examples of quantitative research in social science

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Purpose of Guide
Design Flaws to Avoid
Independent and Dependent Variables
Glossary of Research Terms
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Background Information
The Research Problem/Question
Theoretical Framework
Citation Tracking
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Evaluating Sources
Primary Sources
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Tiertiary Sources
Scholarly vs. Popular Publications
Qualitative Methods
Insiderness
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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

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Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Things to keep in mind when reporting the results of a study using quantitative methods :

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
Always tell the reader what to look for in tables and figures .

NOTE: When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
You can summarize vast sources of information and make comparisons across categories and over time; and,
Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
Uses a static and rigid approach and so employs an inflexible process of discovery;
The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
Results provide less detail on behavior, attitudes, and motivation;
Researcher may collect a much narrower and sometimes superficial dataset;
Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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Methodology

What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

What is the demographic makeup of Singapore in 2020?
How has the average temperature changed globally over the last century?
Does environmental pollution affect the prevalence of honey bees?
Does working from home increase productivity for people with long commutes?

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

In descriptive research , you simply seek an overall summary of your study variables.
In correlational research , you investigate relationships between your study variables.
In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

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Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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Quantitative Methods for the Social Sciences

A Practical Introduction with Examples in SPSS and Stata

Daniel Stockemer ORCID: https://orcid.org/0000-0003-3502-6828 0

School of Political Studies, University of Ottawa, Ottawa, Canada

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Offers an essential introduction to survey research and quantitative methods
Teaches statistical methods in a practical, hands-on manner
Shows how to conduct empirical tests in SPSS and Stata

1.42m Accesses

93 Citations

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Table of contents (9 chapters)

Front matter, introduction.

Daniel Stockemer

The Nuts and Bolts of Empirical Social Science

A short introduction to survey research, constructing a survey, conducting a survey, univariate statistics, bivariate statistics with categorical variables, bivariate relationships featuring two continuous variables, multivariate regression analysis, back matter.

Quantitative Methods in Social Sciences
Statistics in Social Sciences
Practical Approach to Survey Research
Introductory Statistics

Book Title : Quantitative Methods for the Social Sciences

Book Subtitle : A Practical Introduction with Examples in SPSS and Stata

Authors : Daniel Stockemer

DOI : https://doi.org/10.1007/978-3-319-99118-4

Publisher : Springer Cham

eBook Packages : Social Sciences , Social Sciences (R0)

eBook ISBN : 978-3-319-99118-4 Published: 19 November 2018

Edition Number : 1

Number of Pages : IX, 181

Number of Illustrations : 27 b/w illustrations, 93 illustrations in colour

Topics : Methodology of the Social Sciences , Statistics for Social Sciences, Humanities, Law , Statistics and Computing/Statistics Programs

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Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

Anol Bhattacherjee, University of South Florida

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

Formats Available

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Learn more about reviews.

Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

About the book.

Part I. Main Body

Science and scientific research
Thinking like a researcher
The research process
Theories in scientific research
Research design
Measurement of constructs
Scale reliability and validity
Survey research
Experimental research
Case research
Interpretive research
Qualitative analysis
Quantitative analysis: Descriptive statistics
Quantitative analysis: Inferential statistics
Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline, MIS Quarterly and Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of MIS Quarterly for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at http://ab2020.weebly.com .

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What is social science?

Quantitative research.

Quantitative research can measure and describe whole societies, or institutions, organisations or groups of individuals that are part of them. The strength of quantitative methods is that they can provide vital information about a society or community, through surveys, examinations, records or censuses, that no individual could obtain by observation.

Quantitative methodologies

Some of the most common quantitative research methodologies are described here. These methodologies are widely used in research funded by the Economic and Social Research Council (ESRC).

Cross-sectional studies

Cross-sectional studies are surveys undertaken at one point in time, rather like a photo taken by a camera. If the same or similar survey is repeated, we can get good measures of how society is changing.

Longitudinal studies

Longitudinal studies follow the same respondents over an extended period of time. They can employ both qualitative and quantitative research methods, and they follow the same group of people over time. For example, the Millennium Cohort Study has been keeping track of more than 11,000 children born between 2000 and 2002. Some of its many findings have shown how childhood factors such as poverty and birth weight can affect health and success at school as children get older.

Opinion polls

An opinion poll is a form of survey designed to measure the opinions of a target population about an issue, such as support for political parties and views about crime and justice, the economy or the environment.

Questionnaires

Questionnaires collect data in a standardised way, so that useful summaries can be made about large groups of respondents, such as the proportion of all young people of a given age who are bullied. Usually most questions are ‘closed response’, where respondents are given a range of options to choose from. Researchers have to be careful that the questions are not ‘leading’, that the options are comprehensive (they cover every possible answer) and are mutually exclusive, so that only one answer is correct for any respondent.

Social attitude surveys

Social attitude surveys ask more general questions about beliefs and behaviour, for example, how often people go to church, how much trust they have in the police force, whether they think children need a strict upbringing, how content they are with their life, how often they see other family members, and whether they are in employment.

Surveys and censuses

A census is a survey of everyone in the population. Because of the vast number of respondents, they are very expensive to organise. Governments now depend much more on sample surveys and administrative records, for example those created by a stay in hospital or tax returns. Surveys use a questionnaire to investigate respondents in a sample. Samples are chosen in such a way that they can represent a much larger population. A precise calculation can be made of how accurate the information from any sample is likely to be.

Further information

See our social science for schools resource page on the UK Government Web Archive for more information on social science methodologies.

Last updated: 31 March 2022

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J Korean Med Sci
v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

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Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

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EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

Social Sciences Research: Qualitative vs. Quantitative Research

What is Social Science?

Qualitative vs. Quantitative Research

Scholarly vs. Popular Sources This link opens in a new window
Evaluating Sources This link opens in a new window
Social Research Organizations
Anatomy of an APA Article
Social Sciences Databases
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Focus Groups

Social science research, or social research as it is sometimes called, stems from the natural sciences, and similar to its precursory field, it uses empirical, measurable outcomes to arrive at a conclusion. While natural scientists use the scientific method, social scientists often use quantitative research to go about their method of discovery.

Quantitative research "is the systematic examination of social phenomena, using statistical models and mathematical theories to develop, accumulate, and refine the scientific knowledge base" (" Quantitative Research," 2008 ). Quantitative research also provides "generalizable" findings, and according to Marlow (1993), is "characterized by hypothesis testing, using large samples, standardized measures, a deductive approach, and rigorously structured data collection instruments" (cited in "Quantitative Research").

As an alternative to quantitative research, qualitative research is also employed in social science research and is contrasted with quantitative research as such:

Insider rather than outsider
Person-centered rather than variable-centered
Holistic rather than particularistic
Depth rather than breadth

(" Qualitative Research, " 2008)

Trochim (2006), however, warns that researchers should not become so caught up in the polarizing differences between qualitative and quantiative research. He writes, "All quantitative data is based upon qualitative judgments; and all qualitative data can be described and manipulated numerically" (para. 3).

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Doing Quantitative Research in the Social Sciences An Integrated Approach to Research Design, Measurement and Statistics

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`There is much that is excellent about this book. If all educational researchers had studied it thoroughly, especially the sections on research design, representative samples and confounding variables, then there might be less publication of sweeping statements based on insufficient evidence' - British Educational Research Journal

Very nice and readable book. I recommend it to all my students and refer to it frequently in my teaching

Not an easy read for novices

I personally found this book a very interesting read, but unfortunately this is not pitched at an appropriate level for our students. This is not a comment on the book, rather the structure of our course(s) and the outputs that our students are expected to produce. Many thanks.

Doing quantitative research in the social sciences an integrated approach to research design, measurement and statistics contains 22 chapters which are divided into six main parts. Part one introduction to research design consists of seven chapters which introduce the reader to the nature of data in terms of its multiple sources and discusses the differences between empirical and non-empirical approaches to gathering data, as well as the advantage of using a scientific approach to conducting research with respect to using rigorous and methodical processes and techniques. Also, covered in part one are the issues researchers face when planning and designing research with regards to answering research questions and providing evidence of the validity of hypotheses being tested, in addition to working with and measuring variables. This section concludes with what the researcher should consider when identifying population(s) from which to sample from and part one presents a summary of the techniques which can be employed when selecting a sampling strategy, as well as key issues to consider associated with each sample strategy. Part two measurement design consists of four chapters which focus mainly on attitude surveys measuring attitudes, opinions and views in relation to what the results from these types of instruments indicate and reveal about a given area or phenomena. Also covered in this section is the importance of construct validity with respect to enhancing the reliability of research designed instruments for gathering and measuring data, in addition to, checking the reliability and validity of instruments. Part three turning data into information using statistics consists of three chapters which discuss the advantages of using a spreadsheet to generate frequency tables, graphs and charts, as well as how to prepare data for comparing different groups of data. The theory discussed within this section relate to probability and statistical significance with respect to the types of data which can be analysed and the effect the distribution of the data can have on the results in relation to the degree which statistical inference can be inferred. The effect that power and errors can have on data with regards to setting up significance levels and testing hypotheses are also covered in this section. Part four ex post facto, experimental and quasi-experimental designs: parametric tests consists of four chapters and discuss the differences between experimental and quasi-experimental research designs and the types of parametric tests which can be applied when analysing and interpreting data generated from making comparisons between groups when comparing means differences. Part five nonparametric tests: nominal and ordinal variables consists of two chapters which present an alternative to using parametric tests and discusses when to use nonparametric tests and the types of tests that can be used as a nonparametric equivalent to parametric tests for comparing medians as apposed to means differences. Part six describing non-causal relationships consists of two chapters which cover correlation and the differences between experimental and nonexperimental research and when correlation should be used, as well as the benefits of using scatter diagrams to aid in the interpretation of correlations by representing the results graphically to determine the strength of the relationship between two variables. Regression and linear regression equations are discussed in relation to mathematical theory, a well as using two dimensional and three dimensional scatter diagrams to display frequencies and standard deviations. Appendix provides a useful introduction to using spreadsheets for presenting data analysed diagrammatically and how to amend or update information to a completed spreadsheet of data. The appendix also presents a helpful set of statistical tables showing: (1) areas under the normal distribution; (2) critical values for significance for a one-tailed test; (3) critical values for the F-distribution; (4) critical values for F-distribution as well as other useful tables. A glossary of mathematical symbols, equations and excel functions along with a definition and description of their function are provided, as well as a bibliography of helpful references. Helpful check lists are provided within chapters for the reader to check their knowledge and understanding of the information being presented in chapters. This text covers the theory behind conducting quantitative research in the social sciences. The main focus of this book is on the theory underpinning research design and analysis using statistical techniques to test data gathered from survey questionnaires. The reading level of this text is accessible for undergraduate, postgraduate and doctorial students, as well as researchers working with quantitative data on research projects. This book is recommended as essential reading and reference material for anyone using a quantitative approach to research within the social science.

A well written text-book that gives learners and teachers of quantitative research an in-depth understanding of the quantitative paradigm.

Provides a good overview of all statistical methods

This book has met my expectations, additionaly I would be happy if it has SPSS applications, but excel applications are also fine. Thanks for sending it. I'll benefit it for my course.

Budget cuts have forced us to not adopt a BSN program at this time.

this text is recommended for student much further in their masters degree study. it is very detailed and includes some intense statistical tests. I have made my students aware of it to consult as they progress through the masters level programme

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4.3 Quantitative research questions

Learning objectives.

Describe how research questions for exploratory, descriptive, and explanatory quantitative questions differ and how to phrase them
Identify the differences between and provide examples of strong and weak explanatory research questions

Quantitative descriptive questions

The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, “What is the average student debt load of MSW students?” is a descriptive question—and an important one. We aren’t trying to build a causal relationship here. We’re simply trying to describe how much debt MSW students carry. Quantitative descriptive questions like this one are helpful in social work practice as part of community scans, in which human service agencies survey the various needs of the community they serve. If the scan reveals that the community requires more services related to housing, child care, or day treatment for people with disabilities, a nonprofit office can use the community scan to create new programs that meet a defined community need.

an illuminated street sign that reads "ask"

Quantitative descriptive questions will often ask for percentage, count the number of instances of a phenomenon, or determine an average. Descriptive questions may only include one variable, such as ours about debt load, or they may include multiple variables. Because these are descriptive questions, we cannot investigate causal relationships between variables. To do that, we need to use a quantitative explanatory question.

Quantitative explanatory questions

Most studies you read in the academic literature will be quantitative and explanatory. Why is that? Explanatory research tries to build something called nomothetic causal explanations.Matthew DeCarlo says “com[ing]up with a broad, sweeping explanation that is universally true for all people” is the hallmark of nomothetic causal relationships (DeCarlo, 2018, chapter 7.2, para 5 ). They are generalizable across space and time, so they are applicable to a wide audience. The editorial board of a journal wants to make sure their content will be useful to as many people as possible, so it’s not surprising that quantitative research dominates the academic literature.

Structurally, quantitative explanatory questions must contain an independent variable and dependent variable. Questions should ask about the relation between these variables. A standard format for an explanatory quantitative research question is: “What is the relation between [independent variable] and [dependent variable] for [target population]?” You should play with the wording for your research question, revising it as you see fit. The goal is to make the research question reflect what you really want to know in your study.

Let’s take a look at a few more examples of possible research questions and consider the relative strengths and weaknesses of each. Table 4.1 does just that. While reading the table, keep in mind that it only includes some of the most relevant strengths and weaknesses of each question. Certainly each question may have additional strengths and weaknesses not noted in the table.

Making it more specific

A good research question should also be specific and clear about the concepts it addresses. A group of students investigating gender and household tasks knows what they mean by “household tasks.” You likely also have an impression of what “household tasks” means. But are your definition and the students’ definition the same? A participant in their study may think that managing finances and performing home maintenance are household tasks, but the researcher may be interested in other tasks like childcare or cleaning. The only way to ensure your study stays focused and clear is to be specific about what you mean by a concept. The student in our example could pick a specific household task that was interesting to them or that the literature indicated was important—for example, childcare. Or, the student could have a broader view of household tasks, one that encompasses childcare, food preparation, financial management, home repair, and care for relatives. Any option is probably okay, as long as the researchers are clear on what they mean by “household tasks.”

Table 4.2 contains some “watch words” that indicate you may need to be more specific about the concepts in your research question.

It can be challenging in social work research to be this specific, particularly when you are just starting out your investigation of the topic. If you’ve only read one or two articles on the topic, it can be hard to know what you are interested in studying. Broad questions like “What are the causes of chronic homelessness, and what can be done to prevent it?” are common at the beginning stages of a research project. However, social work research demands that you examine the literature on the topic and refine your question over time to be more specific and clear before you begin your study. Perhaps you want to study the effect of a specific anti-homelessness program that you found in the literature. Maybe there is a particular model to fighting homelessness, like Housing First or transitional housing that you want to investigate further. You may want to focus on a potential cause of homelessness such as LGBTQ discrimination that you find interesting or relevant to your practice. As you can see, the possibilities for making your question more specific are almost infinite.

Quantitative exploratory questions

In exploratory research, the researcher doesn’t quite know the lay of the land yet. If someone is proposing to conduct an exploratory quantitative project, the watch words highlighted in Table 4.2 are not problematic at all. In fact, questions such as “What factors influence the removal of children in child welfare cases?” are good because they will explore a variety of factors or causes. In this question, the independent variable is less clearly written, but the dependent variable, family preservation outcomes, is quite clearly written. The inverse can also be true. If we were to ask, “What outcomes are associated with family preservation services in child welfare?”, we would have a clear independent variable, family preservation services, but an unclear dependent variable, outcomes. Because we are only conducting exploratory research on a topic, we may not have an idea of what concepts may comprise our “outcomes” or “factors.” Only after interacting with our participants will we be able to understand which concepts are important.

Key Takeaways

Quantitative descriptive questions are helpful for community scans but cannot investigate causal relationships between variables.
Quantitative explanatory questions must include an independent and dependent variable.

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Guidebook for Social Work Literature Reviews and Research Questions Copyright © 2020 by Rebecca Mauldin and Matthew DeCarlo is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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500+ Quantitative Research Titles and Topics

Table of Contents

Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology , economics , and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas to explore, from analyzing data on a specific population to studying the effects of a particular intervention or treatment. In this post, we will provide some ideas for quantitative research topics that may inspire you and help you narrow down your interests.

Quantitative Research Titles

Quantitative Research Titles are as follows:

Business and Economics

“Statistical Analysis of Supply Chain Disruptions on Retail Sales”
“Quantitative Examination of Consumer Loyalty Programs in the Fast Food Industry”
“Predicting Stock Market Trends Using Machine Learning Algorithms”
“Influence of Workplace Environment on Employee Productivity: A Quantitative Study”
“Impact of Economic Policies on Small Businesses: A Regression Analysis”
“Customer Satisfaction and Profit Margins: A Quantitative Correlation Study”
“Analyzing the Role of Marketing in Brand Recognition: A Statistical Overview”
“Quantitative Effects of Corporate Social Responsibility on Consumer Trust”
“Price Elasticity of Demand for Luxury Goods: A Case Study”
“The Relationship Between Fiscal Policy and Inflation Rates: A Time-Series Analysis”
“Factors Influencing E-commerce Conversion Rates: A Quantitative Exploration”
“Examining the Correlation Between Interest Rates and Consumer Spending”
“Standardized Testing and Academic Performance: A Quantitative Evaluation”
“Teaching Strategies and Student Learning Outcomes in Secondary Schools: A Quantitative Study”
“The Relationship Between Extracurricular Activities and Academic Success”
“Influence of Parental Involvement on Children’s Educational Achievements”
“Digital Literacy in Primary Schools: A Quantitative Assessment”
“Learning Outcomes in Blended vs. Traditional Classrooms: A Comparative Analysis”
“Correlation Between Teacher Experience and Student Success Rates”
“Analyzing the Impact of Classroom Technology on Reading Comprehension”
“Gender Differences in STEM Fields: A Quantitative Analysis of Enrollment Data”
“The Relationship Between Homework Load and Academic Burnout”
“Assessment of Special Education Programs in Public Schools”
“Role of Peer Tutoring in Improving Academic Performance: A Quantitative Study”

Medicine and Health Sciences

“The Impact of Sleep Duration on Cardiovascular Health: A Cross-sectional Study”
“Analyzing the Efficacy of Various Antidepressants: A Meta-Analysis”
“Patient Satisfaction in Telehealth Services: A Quantitative Assessment”
“Dietary Habits and Incidence of Heart Disease: A Quantitative Review”
“Correlations Between Stress Levels and Immune System Functioning”
“Smoking and Lung Function: A Quantitative Analysis”
“Influence of Physical Activity on Mental Health in Older Adults”
“Antibiotic Resistance Patterns in Community Hospitals: A Quantitative Study”
“The Efficacy of Vaccination Programs in Controlling Disease Spread: A Time-Series Analysis”
“Role of Social Determinants in Health Outcomes: A Quantitative Exploration”
“Impact of Hospital Design on Patient Recovery Rates”
“Quantitative Analysis of Dietary Choices and Obesity Rates in Children”

Social Sciences

“Examining Social Inequality through Wage Distribution: A Quantitative Study”
“Impact of Parental Divorce on Child Development: A Longitudinal Study”
“Social Media and its Effect on Political Polarization: A Quantitative Analysis”
“The Relationship Between Religion and Social Attitudes: A Statistical Overview”
“Influence of Socioeconomic Status on Educational Achievement”
“Quantifying the Effects of Community Programs on Crime Reduction”
“Public Opinion and Immigration Policies: A Quantitative Exploration”
“Analyzing the Gender Representation in Political Offices: A Quantitative Study”
“Impact of Mass Media on Public Opinion: A Regression Analysis”
“Influence of Urban Design on Social Interactions in Communities”
“The Role of Social Support in Mental Health Outcomes: A Quantitative Analysis”
“Examining the Relationship Between Substance Abuse and Employment Status”

Engineering and Technology

“Performance Evaluation of Different Machine Learning Algorithms in Autonomous Vehicles”
“Material Science: A Quantitative Analysis of Stress-Strain Properties in Various Alloys”
“Impacts of Data Center Cooling Solutions on Energy Consumption”
“Analyzing the Reliability of Renewable Energy Sources in Grid Management”
“Optimization of 5G Network Performance: A Quantitative Assessment”
“Quantifying the Effects of Aerodynamics on Fuel Efficiency in Commercial Airplanes”
“The Relationship Between Software Complexity and Bug Frequency”
“Machine Learning in Predictive Maintenance: A Quantitative Analysis”
“Wearable Technologies and their Impact on Healthcare Monitoring”
“Quantitative Assessment of Cybersecurity Measures in Financial Institutions”
“Analysis of Noise Pollution from Urban Transportation Systems”
“The Influence of Architectural Design on Energy Efficiency in Buildings”

Quantitative Research Topics

Quantitative Research Topics are as follows:

The effects of social media on self-esteem among teenagers.
A comparative study of academic achievement among students of single-sex and co-educational schools.
The impact of gender on leadership styles in the workplace.
The correlation between parental involvement and academic performance of students.
The effect of mindfulness meditation on stress levels in college students.
The relationship between employee motivation and job satisfaction.
The effectiveness of online learning compared to traditional classroom learning.
The correlation between sleep duration and academic performance among college students.
The impact of exercise on mental health among adults.
The relationship between social support and psychological well-being among cancer patients.
The effect of caffeine consumption on sleep quality.
A comparative study of the effectiveness of cognitive-behavioral therapy and pharmacotherapy in treating depression.
The relationship between physical attractiveness and job opportunities.
The correlation between smartphone addiction and academic performance among high school students.
The impact of music on memory recall among adults.
The effectiveness of parental control software in limiting children’s online activity.
The relationship between social media use and body image dissatisfaction among young adults.
The correlation between academic achievement and parental involvement among minority students.
The impact of early childhood education on academic performance in later years.
The effectiveness of employee training and development programs in improving organizational performance.
The relationship between socioeconomic status and access to healthcare services.
The correlation between social support and academic achievement among college students.
The impact of technology on communication skills among children.
The effectiveness of mindfulness-based stress reduction programs in reducing symptoms of anxiety and depression.
The relationship between employee turnover and organizational culture.
The correlation between job satisfaction and employee engagement.
The impact of video game violence on aggressive behavior among children.
The effectiveness of nutritional education in promoting healthy eating habits among adolescents.
The relationship between bullying and academic performance among middle school students.
The correlation between teacher expectations and student achievement.
The impact of gender stereotypes on career choices among high school students.
The effectiveness of anger management programs in reducing violent behavior.
The relationship between social support and recovery from substance abuse.
The correlation between parent-child communication and adolescent drug use.
The impact of technology on family relationships.
The effectiveness of smoking cessation programs in promoting long-term abstinence.
The relationship between personality traits and academic achievement.
The correlation between stress and job performance among healthcare professionals.
The impact of online privacy concerns on social media use.
The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
The relationship between teacher feedback and student motivation.
The correlation between physical activity and academic performance among elementary school students.
The impact of parental divorce on academic achievement among children.
The effectiveness of diversity training in improving workplace relationships.
The relationship between childhood trauma and adult mental health.
The correlation between parental involvement and substance abuse among adolescents.
The impact of social media use on romantic relationships among young adults.
The effectiveness of assertiveness training in improving communication skills.
The relationship between parental expectations and academic achievement among high school students.
The correlation between sleep quality and mood among adults.
The impact of video game addiction on academic performance among college students.
The effectiveness of group therapy in treating eating disorders.
The relationship between job stress and job performance among teachers.
The correlation between mindfulness and emotional regulation.
The impact of social media use on self-esteem among college students.
The effectiveness of parent-teacher communication in promoting academic achievement among elementary school students.
The impact of renewable energy policies on carbon emissions
The relationship between employee motivation and job performance
The effectiveness of psychotherapy in treating eating disorders
The correlation between physical activity and cognitive function in older adults
The effect of childhood poverty on adult health outcomes
The impact of urbanization on biodiversity conservation
The relationship between work-life balance and employee job satisfaction
The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating trauma
The correlation between parenting styles and child behavior
The effect of social media on political polarization
The impact of foreign aid on economic development
The relationship between workplace diversity and organizational performance
The effectiveness of dialectical behavior therapy in treating borderline personality disorder
The correlation between childhood abuse and adult mental health outcomes
The effect of sleep deprivation on cognitive function
The impact of trade policies on international trade and economic growth
The relationship between employee engagement and organizational commitment
The effectiveness of cognitive therapy in treating postpartum depression
The correlation between family meals and child obesity rates
The effect of parental involvement in sports on child athletic performance
The impact of social entrepreneurship on sustainable development
The relationship between emotional labor and job burnout
The effectiveness of art therapy in treating dementia
The correlation between social media use and academic procrastination
The effect of poverty on childhood educational attainment
The impact of urban green spaces on mental health
The relationship between job insecurity and employee well-being
The effectiveness of virtual reality exposure therapy in treating anxiety disorders
The correlation between childhood trauma and substance abuse
The effect of screen time on children’s social skills
The impact of trade unions on employee job satisfaction
The relationship between cultural intelligence and cross-cultural communication
The effectiveness of acceptance and commitment therapy in treating chronic pain
The correlation between childhood obesity and adult health outcomes
The effect of gender diversity on corporate performance
The impact of environmental regulations on industry competitiveness.
The impact of renewable energy policies on greenhouse gas emissions
The relationship between workplace diversity and team performance
The effectiveness of group therapy in treating substance abuse
The correlation between parental involvement and social skills in early childhood
The effect of technology use on sleep patterns
The impact of government regulations on small business growth
The relationship between job satisfaction and employee turnover
The effectiveness of virtual reality therapy in treating anxiety disorders
The correlation between parental involvement and academic motivation in adolescents
The effect of social media on political engagement
The impact of urbanization on mental health
The relationship between corporate social responsibility and consumer trust
The correlation between early childhood education and social-emotional development
The effect of screen time on cognitive development in young children
The impact of trade policies on global economic growth
The relationship between workplace diversity and innovation
The effectiveness of family therapy in treating eating disorders
The correlation between parental involvement and college persistence
The effect of social media on body image and self-esteem
The impact of environmental regulations on business competitiveness
The relationship between job autonomy and job satisfaction
The effectiveness of virtual reality therapy in treating phobias
The correlation between parental involvement and academic achievement in college
The effect of social media on sleep quality
The impact of immigration policies on social integration
The relationship between workplace diversity and employee well-being
The effectiveness of psychodynamic therapy in treating personality disorders
The correlation between early childhood education and executive function skills
The effect of parental involvement on STEM education outcomes
The impact of trade policies on domestic employment rates
The relationship between job insecurity and mental health
The effectiveness of exposure therapy in treating PTSD
The correlation between parental involvement and social mobility
The effect of social media on intergroup relations
The impact of urbanization on air pollution and respiratory health.
The relationship between emotional intelligence and leadership effectiveness
The effectiveness of cognitive-behavioral therapy in treating depression
The correlation between early childhood education and language development
The effect of parental involvement on academic achievement in STEM fields
The impact of trade policies on income inequality
The relationship between workplace diversity and customer satisfaction
The effectiveness of mindfulness-based therapy in treating anxiety disorders
The correlation between parental involvement and civic engagement in adolescents
The effect of social media on mental health among teenagers
The impact of public transportation policies on traffic congestion
The relationship between job stress and job performance
The effectiveness of group therapy in treating depression
The correlation between early childhood education and cognitive development
The effect of parental involvement on academic motivation in college
The impact of environmental regulations on energy consumption
The relationship between workplace diversity and employee engagement
The effectiveness of art therapy in treating PTSD
The correlation between parental involvement and academic success in vocational education
The effect of social media on academic achievement in college
The impact of tax policies on economic growth
The relationship between job flexibility and work-life balance
The effectiveness of acceptance and commitment therapy in treating anxiety disorders
The correlation between early childhood education and social competence
The effect of parental involvement on career readiness in high school
The impact of immigration policies on crime rates
The relationship between workplace diversity and employee retention
The effectiveness of play therapy in treating trauma
The correlation between parental involvement and academic success in online learning
The effect of social media on body dissatisfaction among women
The impact of urbanization on public health infrastructure
The relationship between job satisfaction and job performance
The effectiveness of eye movement desensitization and reprocessing therapy in treating PTSD
The correlation between early childhood education and social skills in adolescence
The effect of parental involvement on academic achievement in the arts
The impact of trade policies on foreign investment
The relationship between workplace diversity and decision-making
The effectiveness of exposure and response prevention therapy in treating OCD
The correlation between parental involvement and academic success in special education
The impact of zoning laws on affordable housing
The relationship between job design and employee motivation
The effectiveness of cognitive rehabilitation therapy in treating traumatic brain injury
The correlation between early childhood education and social-emotional learning
The effect of parental involvement on academic achievement in foreign language learning
The impact of trade policies on the environment
The relationship between workplace diversity and creativity
The effectiveness of emotion-focused therapy in treating relationship problems
The correlation between parental involvement and academic success in music education
The effect of social media on interpersonal communication skills
The impact of public health campaigns on health behaviors
The relationship between job resources and job stress
The effectiveness of equine therapy in treating substance abuse
The correlation between early childhood education and self-regulation
The effect of parental involvement on academic achievement in physical education
The impact of immigration policies on cultural assimilation
The relationship between workplace diversity and conflict resolution
The effectiveness of schema therapy in treating personality disorders
The correlation between parental involvement and academic success in career and technical education
The effect of social media on trust in government institutions
The impact of urbanization on public transportation systems
The relationship between job demands and job stress
The correlation between early childhood education and executive functioning
The effect of parental involvement on academic achievement in computer science
The effectiveness of cognitive processing therapy in treating PTSD
The correlation between parental involvement and academic success in homeschooling
The effect of social media on cyberbullying behavior
The impact of urbanization on air quality
The effectiveness of dance therapy in treating anxiety disorders
The correlation between early childhood education and math achievement
The effect of parental involvement on academic achievement in health education
The impact of global warming on agriculture
The effectiveness of narrative therapy in treating depression
The correlation between parental involvement and academic success in character education
The effect of social media on political participation
The impact of technology on job displacement
The relationship between job resources and job satisfaction
The effectiveness of art therapy in treating addiction
The correlation between early childhood education and reading comprehension
The effect of parental involvement on academic achievement in environmental education
The impact of income inequality on social mobility
The relationship between workplace diversity and organizational culture
The effectiveness of solution-focused brief therapy in treating anxiety disorders
The correlation between parental involvement and academic success in physical therapy education
The effect of social media on misinformation
The impact of green energy policies on economic growth
The relationship between job demands and employee well-being
The correlation between early childhood education and science achievement
The effect of parental involvement on academic achievement in religious education
The impact of gender diversity on corporate governance
The relationship between workplace diversity and ethical decision-making
The correlation between parental involvement and academic success in dental hygiene education
The effect of social media on self-esteem among adolescents
The impact of renewable energy policies on energy security
The effect of parental involvement on academic achievement in social studies
The impact of trade policies on job growth
The relationship between workplace diversity and leadership styles
The correlation between parental involvement and academic success in online vocational training
The effect of social media on self-esteem among men
The impact of urbanization on air pollution levels
The effectiveness of music therapy in treating depression
The correlation between early childhood education and math skills
The effect of parental involvement on academic achievement in language arts
The impact of immigration policies on labor market outcomes
The effectiveness of hypnotherapy in treating phobias
The effect of social media on political engagement among young adults
The impact of urbanization on access to green spaces
The relationship between job crafting and job satisfaction
The effectiveness of exposure therapy in treating specific phobias
The correlation between early childhood education and spatial reasoning
The effect of parental involvement on academic achievement in business education
The impact of trade policies on economic inequality
The effectiveness of narrative therapy in treating PTSD
The correlation between parental involvement and academic success in nursing education
The effect of social media on sleep quality among adolescents
The impact of urbanization on crime rates
The relationship between job insecurity and turnover intentions
The effectiveness of pet therapy in treating anxiety disorders
The correlation between early childhood education and STEM skills
The effect of parental involvement on academic achievement in culinary education
The impact of immigration policies on housing affordability
The relationship between workplace diversity and employee satisfaction
The effectiveness of mindfulness-based stress reduction in treating chronic pain
The correlation between parental involvement and academic success in art education
The effect of social media on academic procrastination among college students
The impact of urbanization on public safety services.

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(PDF) Quantitative vs. Qualitative Research in Social Science
Importance of Quantitative Research Across Fields
Chapter 3
A Quick Guide to Quantitative Research in the Social Sciences
Quantitative Social Science
(PDF) EMBARKING ON RESEARCH IN THE SOCIAL SCIENCES: UNDERSTANDING THE

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Sample Qualitative and Quantitative Research Titles
Quantitative and Qualitative Methods
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Before-and-after Study Design
Four Types of Quantitative Research
Sociology Lecture #23 Qualitative and Quantitative Analysis

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Quantitative Methods
Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques.Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.
A Quick Guide to Quantitative Research in the Social Sciences
This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for ...
What Is Quantitative Research?
Quantitative research is the opposite of qualitative research, which involves collecting and analyzing non-numerical data (e.g., text, video, or audio). Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc. Quantitative research question examples
Quantitative Analysis in Social Sciences: An Brief ...
In this paper, I present an introduction to quantitative research methods in social sciences. The paper is intended for non-Economics undergraduate students, development researchers and ...
PDF A Quick Guide to Quantitative Research in the Social Sciences
advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you are a qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real ...
A Quick Guide to Quantitative Research in the Social Sciences A Quick
Adherents to the quantitative paradigm align with a positivistic philosophy in which social phenomena should be observable and measurable in a similar manner to those studied in the physical ...
Quantitative Methods for the Social Sciences
The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions onhow to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
The SAGE Handbook of Quantitative Methodology for the Social Sciences
Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource. Indispensable to the teaching, study, and research of quantitative methods. Provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method.
PDF Quantitative Social Science: An Introduction
Quantitative social science is an interdisciplinary ﬁeld encompassing a large number of disciplines, including economics, education, political science, public policy, psy-chology, and sociology. In quantitative social science research, scholars analyze data to understand and solve problems about society and human behavior. For example,
PDF Introduction to quantitative research
Introduction to quantitative research 1.1. What is quantitative research? Research methods in education (and the other social sciences) are often divided into two main types: quantitative and qualitative methods. This book will discuss one of these two main strands: 'quantitative methods', and what distinguishes quantitative from ...
Social Science Research: Principles, Methods and Practices
This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any ...
Quantitative research
Quantitative research. Quantitative research can measure and describe whole societies, or institutions, organisations or groups of individuals that are part of them. The strength of quantitative methods is that they can provide vital information about a society or community, through surveys, examinations, records or censuses, that no individual ...
A Practical Guide to Writing Quantitative and Qualitative Research
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
Quantitative Research in Sociology
The quantitative study definition in sociology research necessitates the use of statistical data, comparative methods, and field methods to study social relationships and cultural institutions ...
Quantitative Research
Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions. ... Examples of Quantitative ...
Social Sciences Research: Qualitative vs. Quantitative Research
Social science research, or social research as it is sometimes called, stems from the natural sciences, and similar to its precursory field, it uses empirical, measurable outcomes to arrive at a conclusion. While natural scientists use the scientific method, social scientists often use quantitative research to go about their method of discovery.
The impact of quantitative research in social work
The importance of quantitative research in the social sciences generally and social work specifically has been highlighted in recent years, in both an international and a British context. Consensus opinion in the UK is that quantitative work is the 'poor relation' in social work research, leading to a number of initiatives.
Interpretive Quantitative Methods for the Social Sciences
Abstract. Quantitative social science has long been dominated by self-consciously positivist approaches to the philosophy, rhetoric and methodology of research. This article outlines an alternative approach based on interpretive research methods. Interpretative approaches are usually associated with qualitative social science but are equally ...
Doing Quantitative Research in the Social Sciences
Written in a lively, accessible style, the student is introduced to research design issues along with statistical procedures necessary for data analysis that develops the student's analytical skills and decision-making powers. An ideal textbook for students across the social sciences, Doing Quantitative Research in the Social Sciences includes ...
Quantitative Research: A Successful Investigation in Natural and Social
Quantitative research explains phenomena by collecting numerical unchanging d etailed data t hat. are analyzed using mathematically based methods, in particular statistics that pose questions of ...
8.3 Quantitative research questions
Quantitative descriptive questions. The type of research you are conducting will impact the research question that you ask. Quantitative descriptive questions are arguably the easiest types of questions to formulate. For example, "What is the average student debt load of MSW students?" is an important descriptive question.
4.3 Quantitative research questions
The type of research you are conducting will impact the research question that you ask. Probably the easiest questions to think of are quantitative descriptive questions. For example, "What is the average student debt load of MSW students?" is a descriptive question—and an important one. We aren't trying to build a causal relationship here.
500+ Quantitative Research Titles and Topics
Quantitative research involves collecting and analyzing numerical data to identify patterns, trends, and relationships among variables. This method is widely used in social sciences, psychology, economics, and other fields where researchers aim to understand human behavior and phenomena through statistical analysis. If you are looking for a quantitative research topic, there are numerous areas ...