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Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

Surveys : List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

Interviews : Asking open-ended questions verbally to respondents.
Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

Use quantitative research if you want to confirm or test something (a theory or hypothesis )
Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

Average scores ( means )
The number of times a particular answer was given
The correlation or causation between two or more variables
The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
Thematic analysis : Closely examining the data to identify the main themes and patterns
Discourse analysis : Studying how communication works in social contexts

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
Quantitative research
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 .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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Qualitative vs Quantitative Research Methods & Data Analysis

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research, on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human. Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded.

Key Features

Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms.

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
The research aims for objectivity (i.e., without bias) and is separated from the data.
The design of the study is determined before it begins.
For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
Useful for testing and validating already constructed theories.
Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

Designing qualitative research
Methods of data collection and analysis
Introduction to quantitative and qualitative research
Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
Qualitative research in health care: Analysing qualitative data
Qualitative data analysis: the framework approach
Using the framework method for the analysis of
Qualitative data in multi-disciplinary health research
Content Analysis
Grounded Theory
Thematic Analysis

Chapter 20. Presentations

Introduction.

If a tree falls in a forest, and no one is around to hear it, does it make a sound? If a qualitative study is conducted, but it is not presented (in words or text), did it really happen? Perhaps not. Findings from qualitative research are inextricably tied up with the way those findings are presented. These presentations do not always need to be in writing, but they need to happen. Think of ethnographies, for example, and their thick descriptions of a particular culture. Witnessing a culture, taking fieldnotes, talking to people—none of those things in and of themselves convey the culture. Or think about an interview-based phenomenological study. Boxes of interview transcripts might be interesting to read through, but they are not a completed study without the intervention of hours of analysis and careful selection of exemplary quotes to illustrate key themes and final arguments and theories. And unlike much quantitative research in the social sciences, where the final write-up neatly reports the results of analyses, the way the “write-up” happens is an integral part of the analysis in qualitative research. Once again, we come back to the messiness and stubborn unlinearity of qualitative research. From the very beginning, when designing the study, imagining the form of its ultimate presentation is helpful.

Because qualitative researchers are motivated by understanding and conveying meaning, effective communication is not only an essential skill but a fundamental facet of the entire research project. Ethnographers must be able to convey a certain sense of verisimilitude, the appearance of true reality. Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them. And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important. This chapter will address how to organize various kinds of presentations for different audiences so that your results can be appreciated and understood.

In the world of academic science, social or otherwise, the primary audience for a study’s results is usually the academic community, and the primary venue for communicating to this audience is the academic journal. Journal articles are typically fifteen to thirty pages in length (8,000 to 12,000 words). Although qualitative researchers often write and publish journal articles—indeed, there are several journals dedicated entirely to qualitative research [1] —the best writing by qualitative researchers often shows up in books. This is because books, running from 80,000 to 150,000 words in length, allow the researcher to develop the material fully. You have probably read some of these in various courses you have taken, not realizing what they are. I have used examples of such books throughout this text, beginning with the three profiles in the introductory chapter. In some instances, the chapters in these books began as articles in academic journals (another indication that the journal article format somewhat limits what can be said about the study overall).

While the article and the book are “final” products of qualitative research, there are actually a few other presentation formats that are used along the way. At the very beginning of a research study, it is often important to have a written research proposal not just to clarify to yourself what you will be doing and when but also to justify your research to an outside agency, such as an institutional review board (IRB; see chapter 12), or to a potential funder, which might be your home institution, a government funder (such as the National Science Foundation, or NSF), or a private foundation (such as the Gates Foundation). As you get your research underway, opportunities will arise to present preliminary findings to audiences, usually through presentations at academic conferences. These presentations can provide important feedback as you complete your analyses. Finally, if you are completing a degree and looking to find an academic job, you will be asked to provide a “job talk,” usually about your research. These job talks are similar to conference presentations but can run significantly longer.

All the presentations mentioned so far are (mostly) for academic audiences. But qualitative research is also unique in that many of its practitioners don’t want to confine their presentation only to other academics. Qualitative researchers who study particular contexts or cultures might want to report back to the people and places they observed. Those working in the critical tradition might want to raise awareness of a particular issue to as large an audience as possible. Many others simply want everyday, nonacademic people to read their work, because they think it is interesting and important. To reach a wide audience, the final product can look like almost anything—it can be a poem, a blog, a podcast, even a science fiction short story. And if you are very lucky, it can even be a national or international bestseller.

In this chapter, we are going to stick with the more basic quotidian presentations—the academic paper / research proposal, the conference slideshow presentation / job talk, and the conference poster. We’ll also spend a bit of time on incorporating universal design into your presentations and how to create some especially attractive and impactful visual displays.

Researcher Note

What is the best piece of advice you’ve ever been given about conducting qualitative research?

The best advice I’ve received came from my adviser, Alford Young Jr. He told me to find the “Jessi Streib” answer to my research question, not the “Pierre Bourdieu” answer to my research question. In other words, don’t just say how a famous theorist would answer your question; say something original, something coming from you.

—Jessi Streib, author of The Power of the Past and Privilege Lost

Writing about Your Research

The journal article and the research proposal.

Although the research proposal is written before you have actually done your research and the article is written after all data collection and analysis is complete, there are actually many similarities between the two in terms of organization and purpose. The final article will (probably—depends on how much the research question and focus have shifted during the research itself) incorporate a great deal of what was included in a preliminary research proposal. The average lengths of both a proposal and an article are quite similar, with the “front sections” of the article abbreviated to make space for the findings, discussion of findings, and conclusion.

Figure 20.1 shows one model for what to include in an article or research proposal, comparing the elements of each with a default word count for each section. Please note that you will want to follow whatever specific guidelines you have been provided by the venue you are submitting the article/proposal to: the IRB, the NSF, the Journal of Qualitative Research . In fact, I encourage you to adapt the default model as needed by swapping out expected word counts for each section and adding or varying the sections to match expectations for your particular publication venue. [2]

You will notice a few things about the default model guidelines. First, while half of the proposal is spent discussing the research design, this section is shortened (but still included) for the article. There are a few elements that only show up in the proposal (e.g., the limitations section is in the introductory section here—it will be more fully developed in the conclusory section in the article). Obviously, you don’t have findings in the proposal, so this is an entirely new section for the article. Note that the article does not include a data management plan or a timeline—two aspects that most proposals require.

It might be helpful to find and maintain examples of successfully written sections that you can use as models for your own writing. I have included a few of these throughout the textbook and have included a few more at the end of this chapter.

Make an Argument

Some qualitative researchers, particularly those engaged in deep ethnographic research, focus their attention primarily if not exclusively on describing the data. They might even eschew the notion that they should make an “argument” about the data, preferring instead to use thick descriptions to convey interpretations. Bracketing the contrast between interpretation and argument for the moment, most readers will expect you to provide an argument about your data, and this argument will be in answer to whatever research question you eventually articulate (remember, research questions are allowed to shift as you get further into data collection and analysis). It can be frustrating to read a well-developed study with clear and elegant descriptions and no argument. The argument is the point of the research, and if you do not have one, 99 percent of the time, you are not finished with your analysis. Calarco ( 2020 ) suggests you imagine a pyramid, with all of your data forming the basis and all of your findings forming the middle section; the top/point of the pyramid is your argument, “what the patterns in your data tell us about how the world works or ought to work” ( 181 ).

The academic community to which you belong will be looking for an argument that relates to or develops theory. This is the theoretical generalizability promise of qualitative research. An academic audience will want to know how your findings relate to previous findings, theories, and concepts (the literature review; see chapter 9). It is thus vitally important that you go back to your literature review (or develop a new one) and draw those connections in your discussion and/or conclusion. When writing to other audiences, you will still want an argument, although it may not be written as a theoretical one. What do I mean by that? Even if you are not referring to previous literature or developing new theories or adapting older ones, a simple description of your findings is like dumping a lot of leaves in the lap of your audience. They still deserve to know about the shape of the forest. Maybe provide them a road map through it. Do this by telling a clear and cogent story about the data. What is the primary theme, and why is it important? What is the point of your research? [3]

A beautifully written piece of research based on participant observation [and/or] interviews brings people to life, and helps the reader understand the challenges people face. You are trying to use vivid, detailed and compelling words to help the reader really understand the lives of the people you studied. And you are trying to connect the lived experiences of these people to a broader conceptual point—so that the reader can understand why it matters. ( Lareau 2021:259 )

Do not hide your argument. Make it the focal point of your introductory section, and repeat it as often as needed to ensure the reader remembers it. I am always impressed when I see researchers do this well (see, e.g., Zelizer 1996 ).

Here are a few other suggestions for writing your article: Be brief. Do not overwhelm the reader with too many words; make every word count. Academics are particularly prone to “overwriting” as a way of demonstrating proficiency. Don’t. When writing your methods section, think about it as a “recipe for your work” that allows other researchers to replicate if they so wish ( Calarco 2020:186 ). Convey all the necessary information clearly, succinctly, and accurately. No more, no less. [4] Do not try to write from “beginning to end” in that order. Certain sections, like the introductory section, may be the last ones you write. I find the methods section the easiest, so I often begin there. Calarco ( 2020 ) begins with an outline of the analysis and results section and then works backward from there to outline the contribution she is making, then the full introduction that serves as a road map for the writing of all sections. She leaves the abstract for the very end. Find what order best works for you.

Presenting at Conferences and Job Talks

Students and faculty are primarily called upon to publicly present their research in two distinct contexts—the academic conference and the “job talk.” By convention, conference presentations usually run about fifteen minutes and, at least in sociology and other social sciences, rely primarily on the use of a slideshow (PowerPoint Presentation or PPT) presentation. You are usually one of three or four presenters scheduled on the same “panel,” so it is an important point of etiquette to ensure that your presentation falls within the allotted time and does not crowd into that of the other presenters. Job talks, on the other hand, conventionally require a forty- to forty-five-minute presentation with a fifteen- to twenty-minute question and answer (Q&A) session following it. You are the only person presenting, so if you run over your allotted time, it means less time for the Q&A, which can disturb some audience members who have been waiting for a chance to ask you something. It is sometimes possible to incorporate questions during your presentation, which allows you to take the entire hour, but you might end up shorting your presentation this way if the questions are numerous. It’s best for beginners to stick to the “ask me at the end” format (unless there is a simple clarifying question that can easily be addressed and makes the presentation run more smoothly, as in the case where you simply forgot to include information on the number of interviews you conducted).

For slideshows, you should allot two or even three minutes for each slide, never less than one minute. And those slides should be clear, concise, and limited. Most of what you say should not be on those slides at all. The slides are simply the main points or a clear image of what you are speaking about. Include bulleted points (words, short phrases), not full sentences. The exception is illustrative quotations from transcripts or fieldnotes. In those cases, keep to one illustrative quote per slide, and if it is long, bold or otherwise, highlight the words or passages that are most important for the audience to notice. [5]

Figure 20.2 provides a possible model for sections to include in either a conference presentation or a job talk, with approximate times and approximate numbers of slides. Note the importance (in amount of time spent) of both the research design and the findings/results sections, both of which have been helpfully starred for you. Although you don’t want to short any of the sections, these two sections are the heart of your presentation.

Fig 20.2. Suggested Slideshow Times and Number of Slides

Should you write out your script to read along with your presentation? I have seen this work well, as it prevents presenters from straying off topic and keeps them to the time allotted. On the other hand, these presentations can seem stiff and wooden. Personally, although I have a general script in advance, I like to speak a little more informally and engagingly with each slide, sometimes making connections with previous panelists if I am at a conference. This means I have to pay attention to the time, and I sometimes end up breezing through one section more quickly than I would like. Whatever approach you take, practice in advance. Many times. With an audience. Ask for feedback, and pay attention to any presentation issues that arise (e.g., Do you speak too fast? Are you hard to hear? Do you stumble over a particular word or name?).

Even though there are rules and guidelines for what to include, you will still want to make your presentation as engaging as possible in the little amount of time you have. Calarco ( 2020:274 ) recommends trying one of three story structures to frame your presentation: (1) the uncertain explanation , where you introduce a phenomenon that has not yet been fully explained and then describe how your research is tackling this; (2) the uncertain outcome , where you introduce a phenomenon where the consequences have been unclear and then you reveal those consequences with your research; and (3) the evocative example , where you start with some interesting example from your research (a quote from the interview transcripts, for example) or the real world and then explain how that example illustrates the larger patterns you found in your research. Notice that each of these is a framing story. Framing stories are essential regardless of format!

A Word on Universal Design

Please consider accessibility issues during your presentation, and incorporate elements of universal design into your slideshow. The basic idea behind universal design in presentations is that to the greatest extent possible, all people should be able to view, hear, or otherwise take in your presentation without needing special individual adaptations. If you can make your presentation accessible to people with visual impairment or hearing loss, why not do so? For example, one in twelve men is color-blind, unable to differentiate between certain colors, red/green being the most common problem. So if you design a graphic that relies on red and green bars, some of your audience members may not be able to properly identify which bar means what. Simple contrasts of black and white are much more likely to be visible to all members of your audience. There are many other elements of good universal design, but the basic foundation of all of them is that you consider how to make your presentation as accessible as possible at the outset. For example, include captions whenever possible, both as descriptions on slides and as images on slides and for any audio or video clips you are including; keep font sizes large enough to read from the back of the room; and face the audience when you are.

Poster Design

Undergraduate students who present at conferences are often encouraged to present at “poster sessions.” This usually means setting up a poster version of your research in a large hall or convention space at a set period of time—ninety minutes is common. Your poster will be one of dozens, and conference-goers will wander through the space, stopping intermittently at posters that attract them. Those who stop by might ask you questions about your research, and you are expected to be able to talk intelligently for two or three minutes. It’s a fairly easy way to practice presenting at conferences, which is why so many organizations hold these special poster sessions.

A good poster design will be immediately attractive to passersby and clearly and succinctly describe your research methods, findings, and conclusions. Some students have simply shrunk down their research papers to manageable sizes and then pasted them on a poster, all twelve to fifteen pages of them. Don’t do that! Here are some better suggestions: State the main conclusion of your research in large bold print at the top of your poster, on brightly colored (contrasting) paper, and paste in a QR code that links to your full paper online ( Calarco 2020:280 ). Use the rest of the poster board to provide a couple of highlights and details of the study. For an interview-based study, for example, you will want to put in some details about your sample (including number of interviews) and setting and then perhaps one or two key quotes, also distinguished by contrasting color background.

Incorporating Visual Design in Your Presentations

In addition to ensuring that your presentation is accessible to as large an audience as possible, you also want to think about how to display your data in general, particularly how to use charts and graphs and figures. [6] The first piece of advice is, use them! As the saying goes, a picture is worth a thousand words. If you can cut to the chase with a visually stunning display, do so. But there are visual displays that are stunning, and then there are the tired, hard-to-see visual displays that predominate at conferences. You can do better than most presenters by simply paying attention here and committing yourself to a good design. As with model section passages, keep a file of visual displays that work as models for your own presentations. Find a good guidebook to presenting data effectively (Evergreen 2018 , 2019 ; Schwabisch 2021) , and refer to it often.

Let me make a few suggestions here to get you started. First, test every visual display on a friend or colleague to find out how quickly they can understand the point you are trying to convey. As with reading passages aloud to ensure that your writing works, showing someone your display is the quickest way to find out if it works. Second, put the point in the title of the display! When writing for an academic journal, there will be specific conventions of what to include in the title (full description including methods of analysis, sample, dates), but in a public presentation, there are no limiting rules. So you are free to write as your title “Working-Class College Students Are Three Times as Likely as Their Peers to Drop Out of College,” if that is the point of the graphic display. It certainly helps the communicative aspect. Third, use the themes available to you in Excel for creating graphic displays, but alter them to better fit your needs . Consider adding dark borders to bars and columns, for example, so that they appear crisper for your audience. Include data callouts and labels, and enlarge them so they are clearly visible. When duplicative or otherwise unnecessary, drop distracting gridlines and labels on the y-axis (the vertical one). Don’t go crazy adding different fonts, however—keep things simple and clear. Sans serif fonts (those without the little hooks on the ends of letters) read better from a distance. Try to use the same color scheme throughout, even if this means manually changing the colors of bars and columns. For example, when reporting on working-class college students, I use blue bars, while I reserve green bars for wealthy students and yellow bars for students in the middle. I repeat these colors throughout my presentations and incorporate different colors when talking about other items or factors. You can also try using simple grayscale throughout, with pops of color to indicate a bar or column or line that is of the most interest. These are just some suggestions. The point is to take presentation seriously and to pay attention to visual displays you are using to ensure they effectively communicate what you want them to communicate. I’ve included a data visualization checklist from Evergreen ( 2018 ) here.

Ethics of Presentation and Reliability

Until now, all the data you have collected have been yours alone. Once you present the data, however, you are sharing sometimes very intimate information about people with a broader public. You will find yourself balancing between protecting the privacy of those you’ve interviewed and observed and needing to demonstrate the reliability of the study. The more information you provide to your audience, the more they can understand and appreciate what you have found, but this also may pose risks to your participants. There is no one correct way to go about finding the right balance. As always, you have a duty to consider what you are doing and must make some hard decisions.

The most obvious place we see this paradox emerge is when you mask your data to protect the privacy of your participants. It is standard practice to provide pseudonyms, for example. It is such standard practice that you should always assume you are being given a pseudonym when reading a book or article based on qualitative research. When I was a graduate student, I tried to find information on how best to construct pseudonyms but found little guidance. There are some ethical issues here, I think. [7] Do you create a name that has the same kind of resonance as the original name? If the person goes by a nickname, should you use a nickname as a pseudonym? What about names that are ethnically marked (as in, almost all of them)? Is there something unethical about reracializing a person? (Yes!) In her study of adolescent subcultures, Wilkins ( 2008 ) noted, “Because many of the goths used creative, alternative names rather than their given names, I did my best to reproduce the spirit of their chosen names” ( 24 ).

Your reader or audience will want to know all the details about your participants so that they can gauge both your credibility and the reliability of your findings. But how many details are too many? What if you change the name but otherwise retain all the personal pieces of information about where they grew up, and how old they were when they got married, and how many children they have, and whether they made a splash in the news cycle that time they were stalked by their ex-boyfriend? At some point, those details are going to tip over into the zone of potential unmasking. When you are doing research at one particular field site that may be easily ascertained (as when you interview college students, probably at the institution at which you are a student yourself), it is even more important to be wary of providing too many details. You also need to think that your participants might read what you have written, know things about the site or the population from which you drew your interviews, and figure out whom you are talking about. This can all get very messy if you don’t do more than simply pseudonymize the people you interviewed or observed.

There are some ways to do this. One, you can design a study with all of these risks in mind. That might mean choosing to conduct interviews or observations at multiple sites so that no one person can be easily identified. Another is to alter some basic details about your participants to protect their identity or to refuse to provide all the information when selecting quotes . Let’s say you have an interviewee named “Anna” (a pseudonym), and she is a twenty-four-year-old Latina studying to be an engineer. You want to use a quote from Anna about racial discrimination in her graduate program. Instead of attributing the quote to Anna (whom your reader knows, because you’ve already told them, is a twenty-four-year-old Latina studying engineering), you might simply attribute the quote to “Latina student in STEM.” Taking this a step further, you might leave the quote unattributed, providing a list of quotes about racial discrimination by “various students.”

The problem with masking all the identifiers, of course, is that you lose some of the analytical heft of those attributes. If it mattered that Anna was twenty-four (not thirty-four) and that she was a Latina and that she was studying engineering, taking out any of those aspects of her identity might weaken your analysis. This is one of those “hard choices” you will be called on to make! A rather radical and controversial solution to this dilemma is to create composite characters , characters based on the reality of the interviews but fully masked because they are not identifiable with any one person. My students are often very queasy about this when I explain it to them. The more positivistic your approach and the more you see individuals rather than social relationships/structure as the “object” of your study, the more employing composites will seem like a really bad idea. But composites “allow researchers to present complex, situated accounts from individuals” without disclosing personal identities ( Willis 2019 ), and they can be effective ways of presenting theory narratively ( Hurst 2019 ). Ironically, composites permit you more latitude when including “dirty laundry” or stories that could harm individuals if their identities became known. Rather than squeezing out details that could identify a participant, the identities are permanently removed from the details. Great difficulty remains, however, in clearly explaining the theoretical use of composites to your audience and providing sufficient information on the reliability of the underlying data.

There are a host of other ethical issues that emerge as you write and present your data. This is where being reflective throughout the process will help. How and what you share of what you have learned will depend on the social relationships you have built, the audiences you are writing or speaking to, and the underlying animating goals of your study. Be conscious about all of your decisions, and then be able to explain them fully, both to yourself and to those who ask.

Our research is often close to us. As a Black woman who is a first-generation college student and a professional with a poverty/working-class origin, each of these pieces of my identity creates nuances in how I engage in my research, including how I share it out. Because of this, it’s important for us to have people in our lives who we trust who can help us, particularly, when we are trying to share our findings. As researchers, we have been steeped in our work, so we know all the details and nuances. Sometimes we take this for granted, and we might not have shared those nuances in conversation or writing or taken some of this information for granted. As I share my research with trusted friends and colleagues, I pay attention to the questions they ask me or the feedback they give when we talk or when they read drafts.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

Final Comments: Preparing for Being Challenged

Once you put your work out there, you must be ready to be challenged. Science is a collective enterprise and depends on a healthy give and take among researchers. This can be both novel and difficult as you get started, but the more you understand the importance of these challenges, the easier it will be to develop the kind of thick skin necessary for success in academia. Scientists’ authority rests on both the inherent strength of their findings and their ability to convince other scientists of the reliability and validity and value of those findings. So be prepared to be challenged, and recognize this as simply another important aspect of conducting research!

Considering what challenges might be made as you design and conduct your study will help you when you get to the writing and presentation stage. Address probable challenges in your final article, and have a planned response to probable questions in a conference presentation or job talk. The following is a list of common challenges of qualitative research and how you might best address them:

Questions about generalizability . Although qualitative research is not statistically generalizable (and be prepared to explain why), qualitative research is theoretically generalizable. Discuss why your findings here might tell us something about related phenomena or contexts.
Questions about reliability . You probably took steps to ensure the reliability of your findings. Discuss them! This includes explaining the use and value of multiple data sources and defending your sampling and case selections. It also means being transparent about your own position as researcher and explaining steps you took to ensure that what you were seeing was really there.
Questions about replicability. Although qualitative research cannot strictly be replicated because the circumstances and contexts will necessarily be different (if only because the point in time is different), you should be able to provide as much detail as possible about how the study was conducted so that another researcher could attempt to confirm or disconfirm your findings. Also, be very clear about the limitations of your study, as this allows other researchers insight into what future research might be warranted.

None of this is easy, of course. Writing beautifully and presenting clearly and cogently require skill and practice. If you take anything from this chapter, it is to remember that presentation is an important and essential part of the research process and to allocate time for this as you plan your research.

Data Visualization Checklist for Slideshow (PPT) Presentations

Adapted from Evergreen ( 2018 )

Text checklist

Short catchy, descriptive titles (e.g., “Working-class students are three times as likely to drop out of college”) summarize the point of the visual display
Subtitled and annotations provide additional information (e.g., “note: male students also more likely to drop out”)
Text size is hierarchical and readable (titles are largest; axes labels smallest, which should be at least 20points)
Text is horizontal. Audience members cannot read vertical text!
All data labeled directly and clearly: get rid of those “legends” and embed the data in your graphic display
Labels are used sparingly; avoid redundancy (e.g., do not include both a number axis and a number label)

Arrangement checklist

Proportions are accurate; bar charts should always start at zero; don’t mislead the audience!
Data are intentionally ordered (e.g., by frequency counts). Do not leave ragged alphabetized bar graphs!
Axis intervals are equidistant: spaces between axis intervals should be the same unit
Graph is two-dimensional. Three-dimensional and “bevelled” displays are confusing
There is no unwanted decoration (especially the kind that comes automatically through the PPT “theme”). This wastes your space and confuses.

Color checklist

There is an intentional color scheme (do not use default theme)
Color is used to identify key patterns (e.g., highlight one bar in red against six others in greyscale if this is the bar you want the audience to notice)
Color is still legible when printed in black and white
Color is legible for people with color blindness (do not use red/green or yellow/blue combinations)
There is sufficient contrast between text and background (black text on white background works best; be careful of white on dark!)

Lines checklist

Be wary of using gridlines; if you do, mute them (grey, not black)
Allow graph to bleed into surroundings (don’t use border lines)
Remove axis lines unless absolutely necessary (better to label directly)

Overall design checklist

The display highlights a significant finding or conclusion that your audience can ‘”see” relatively quickly
The type of graph (e.g., bar chart, pie chart, line graph) is appropriate for the data. Avoid pie charts with more than three slices!
Graph has appropriate level of precision; if you don’t need decimal places
All the chart elements work together to reinforce the main message

Universal Design Checklist for Slideshow (PPT) Presentations

Include both verbal and written descriptions (e.g., captions on slides); consider providing a hand-out to accompany the presentation
Microphone available (ask audience in back if they can clearly hear)
Face audience; allow people to read your lips
Turn on captions when presenting audio or video clips
Adjust light settings for visibility
Speak slowly and clearly; practice articulation; don’t mutter or speak under your breath (even if you have something humorous to say – say it loud!)
Use Black/White contrasts for easy visibility; or use color contrasts that are real contrasts (do not rely on people being able to differentiate red from green, for example)
Use easy to read font styles and avoid too small font sizes: think about what an audience member in the back row will be able to see and read.
Keep your slides simple: do not overclutter them; if you are including quotes from your interviews, take short evocative snippets only, and bold key words and passages. You should also read aloud each passage, preferably with feeling!

Supplement: Models of Written Sections for Future Reference

Data collection section example.

Interviews were semi structured, lasted between one and three hours, and took place at a location chosen by the interviewee. Discussions centered on four general topics: (1) knowledge of their parent’s immigration experiences; (2) relationship with their parents; (3) understanding of family labor, including language-brokering experiences; and (4) experiences with school and peers, including any future life plans. While conducting interviews, I paid close attention to respondents’ nonverbal cues, as well as their use of metaphors and jokes. I conducted interviews until I reached a point of saturation, as indicated by encountering repeated themes in new interviews (Glaser and Strauss 1967). Interviews were audio recorded, transcribed with each interviewee’s permission, and conducted in accordance with IRB protocols. Minors received permission from their parents before participation in the interview. ( Kwon 2022:1832 )

Justification of Case Selection / Sample Description Section Example

Looking at one profession within one organization and in one geographic area does impose limitations on the generalizability of our findings. However, it also has advantages. We eliminate the problem of interorganizational heterogeneity. If multiple organizations are studied simultaneously, it can make it difficult to discern the mechanisms that contribute to racial inequalities. Even with a single occupation there is considerable heterogeneity, which may make understanding how organizational structure impacts worker outcomes difficult. By using the case of one group of professionals in one religious denomination in one geographic region of the United States, we clarify how individuals’ perceptions and experiences of occupational inequality unfold in relation to a variety of observed and unobserved occupational and contextual factors that might be obscured in a larger-scale study. Focusing on a specific group of professionals allows us to explore and identify ways that formal organizational rules combine with informal processes to contribute to the persistence of racial inequality. ( Eagle and Mueller 2022:1510–1511 )

Ethics Section Example

I asked everyone who was willing to sit for a formal interview to speak only for themselves and offered each of them a prepaid Visa Card worth $25–40. I also offered everyone the opportunity to keep the card and erase the tape completely at any time they were dissatisfied with the interview in any way. No one asked for the tape to be erased; rather, people remarked on the interview being a really good experience because they felt heard. Each interview was professionally transcribed and for the most part the excerpts are literal transcriptions. In a few places, the excerpts have been edited to reduce colloquial features of speech (e.g., you know, like, um) and some recursive elements common to spoken language. A few excerpts were placed into standard English for clarity. I made this choice for the benefit of readers who might otherwise find the insights and ideas harder to parse in the original. However, I have to acknowledge this as an act of class-based violence. I tried to keep the original phrasing whenever possible. ( Pascale 2021:235 )

Quantitative vs. Qualitative Research in Psychology

Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

qualitative and quantitative research presentation

Key Differences

Quantitative Research Methods

Qualitative research methods.

How They Relate

In psychology and other social sciences, researchers are faced with an unresolved question: Can we measure concepts like love or racism the same way we can measure temperature or the weight of a star? Social phenomena⁠—things that happen because of and through human behavior⁠—are especially difficult to grasp with typical scientific models.

At a Glance

Psychologists rely on quantitative and quantitative research to better understand human thought and behavior.

Qualitative research involves collecting and evaluating non-numerical data in order to understand concepts or subjective opinions.
Quantitative research involves collecting and evaluating numerical data.

This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research.

Qualitative Research vs. Quantitative Research

In order to understand qualitative and quantitative psychology research, it can be helpful to look at the methods that are used and when each type is most appropriate.

Psychologists rely on a few methods to measure behavior, attitudes, and feelings. These include:

Self-reports , like surveys or questionnaires
Observation (often used in experiments or fieldwork)
Implicit attitude tests that measure timing in responding to prompts

Most of these are quantitative methods. The result is a number that can be used to assess differences between groups.

However, most of these methods are static, inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" answer rather than a "why" answer.

Sometimes, researchers are more interested in the "why" and the "how." That's where qualitative methods come in.

Qualitative research is about speaking to people directly and hearing their words. It is grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective," and that how humans make meaning is just as important as how much they score on a standardized test.

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte (which maintains that factual knowledge obtained by observation is trustworthy) that it became a "scientific method."

The scientific method follows this general process. A researcher must:

Generate a theory or hypothesis (i.e., predict what might happen in an experiment) and determine the variables needed to answer their question
Develop instruments to measure the phenomenon (such as a survey, a thermometer, etc.)
Develop experiments to manipulate the variables
Collect empirical (measured) data
Analyze data

Quantitative methods are about measuring phenomena, not explaining them.

Quantitative research compares two groups of people. There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the researcher a sense of how the various data points relate to one another.

Basic Assumptions

Quantitative methods assume:

That the world is measurable
That humans can observe objectively
That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research have shown, people behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender , social class, or sexual orientation .

Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies across large groups of people, but they can never describe every case or every experience. In other words, there are always outliers.

Correlation and Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

The study was a true experiment.
The independent variable can be manipulated (for example, researchers cannot manipulate gender, but they can change the primer a study subject sees, such as a picture of nature or of a building).
The dependent variable can be measured through a ratio or a scale.

So when you read a report that "gender was linked to" something (like a behavior or an attitude), remember that gender is NOT a cause of the behavior or attitude. There is an apparent relationship, but the true cause of the difference is hidden.

Pitfalls of Quantitative Research

Quantitative methods are one way to approach the measurement and understanding of human and social phenomena. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences.

Quantitative methods can be helpful when making objective comparisons between groups or when looking for relationships between variables. They can be analyzed statistically, which can be helpful when looking for patterns and relationships.

Qualitative data are not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts, and characteristics. This approach uses interviews, written texts, art, photos, and other materials to make sense of human experiences and to understand what these experiences mean to people.

While quantitative methods ask "what" and "how much," qualitative methods ask "why" and "how."

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree that some questions are too complex or impossible to answer with standardized instruments.

These methods also accept that it is impossible to be completely objective in observing phenomena. Researchers have their own thoughts, attitudes, experiences, and beliefs, and these always color how people interpret results.

Qualitative Approaches

There are many different approaches to qualitative research, with their own philosophical bases. Different approaches are best for different kinds of projects. For example:

Case studies and narrative studies are best for single individuals. These involve studying every aspect of a person's life in great depth.
Phenomenology aims to explain experiences. This type of work aims to describe and explore different events as they are consciously and subjectively experienced.
Grounded theory develops models and describes processes. This approach allows researchers to construct a theory based on data that is collected, analyzed, and compared to reach new discoveries.
Ethnography describes cultural groups. In this approach, researchers immerse themselves in a community or group in order to observe behavior.

Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Some researchers specialize in a single method, but others specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

There is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).

The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

Relationship Between Qualitative and Quantitative Research

It might sound like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs. However, this could not be further from the truth.

These two general methods complement each other. By using both, researchers can gain a fuller, more comprehensive understanding of a phenomenon.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method).

After the survey, the same or other researchers might want to dig deeper into issues brought up by its data. Follow-up questions like "how does it feel when...?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Qualitative and quantitative methods both play an important role in psychology. Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior.

Gough B, Madill A. Subjectivity in psychological science: From problem to prospect . Psychol Methods . 2012;17(3):374-384. doi:10.1037/a0029313

Pearce T. “Science organized”: Positivism and the metaphysical club, 1865–1875 . J Hist Ideas . 2015;76(3):441-465.

Adams G. Context in person, person in context: A cultural psychology approach to social-personality psychology . In: Deaux K, Snyder M, eds. The Oxford Handbook of Personality and Social Psychology . Oxford University Press; 2012:182-208.

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Reeves S, Peller J, Goldman J, Kitto S. Ethnography in qualitative educational research: AMEE Guide No. 80 . Medical Teacher . 2013;35(8):e1365-e1379. doi:10.3109/0142159X.2013.804977

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By Anabelle Bernard Fournier Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

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v.74(8); 2010 Oct 11

Presenting and Evaluating Qualitative Research

The purpose of this paper is to help authors to think about ways to present qualitative research papers in the American Journal of Pharmaceutical Education . It also discusses methods for reviewers to assess the rigour, quality, and usefulness of qualitative research. Examples of different ways to present data from interviews, observations, and focus groups are included. The paper concludes with guidance for publishing qualitative research and a checklist for authors and reviewers.

INTRODUCTION

Policy and practice decisions, including those in education, increasingly are informed by findings from qualitative as well as quantitative research. Qualitative research is useful to policymakers because it often describes the settings in which policies will be implemented. Qualitative research is also useful to both pharmacy practitioners and pharmacy academics who are involved in researching educational issues in both universities and practice and in developing teaching and learning.

Qualitative research involves the collection, analysis, and interpretation of data that are not easily reduced to numbers. These data relate to the social world and the concepts and behaviors of people within it. Qualitative research can be found in all social sciences and in the applied fields that derive from them, for example, research in health services, nursing, and pharmacy. 1 It looks at X in terms of how X varies in different circumstances rather than how big is X or how many Xs are there? 2 Textbooks often subdivide research into qualitative and quantitative approaches, furthering the common assumption that there are fundamental differences between the 2 approaches. With pharmacy educators who have been trained in the natural and clinical sciences, there is often a tendency to embrace quantitative research, perhaps due to familiarity. A growing consensus is emerging that sees both qualitative and quantitative approaches as useful to answering research questions and understanding the world. Increasingly mixed methods research is being carried out where the researcher explicitly combines the quantitative and qualitative aspects of the study. 3 , 4

Like healthcare, education involves complex human interactions that can rarely be studied or explained in simple terms. Complex educational situations demand complex understanding; thus, the scope of educational research can be extended by the use of qualitative methods. Qualitative research can sometimes provide a better understanding of the nature of educational problems and thus add to insights into teaching and learning in a number of contexts. For example, at the University of Nottingham, we conducted in-depth interviews with pharmacists to determine their perceptions of continuing professional development and who had influenced their learning. We also have used a case study approach using observation of practice and in-depth interviews to explore physiotherapists' views of influences on their leaning in practice. We have conducted in-depth interviews with a variety of stakeholders in Malawi, Africa, to explore the issues surrounding pharmacy academic capacity building. A colleague has interviewed and conducted focus groups with students to explore cultural issues as part of a joint Nottingham-Malaysia pharmacy degree program. Another colleague has interviewed pharmacists and patients regarding their expectations before and after clinic appointments and then observed pharmacist-patient communication in clinics and assessed it using the Calgary Cambridge model in order to develop recommendations for communication skills training. 5 We have also performed documentary analysis on curriculum data to compare pharmacist and nurse supplementary prescribing courses in the United Kingdom.

It is important to choose the most appropriate methods for what is being investigated. Qualitative research is not appropriate to answer every research question and researchers need to think carefully about their objectives. Do they wish to study a particular phenomenon in depth (eg, students' perceptions of studying in a different culture)? Or are they more interested in making standardized comparisons and accounting for variance (eg, examining differences in examination grades after changing the way the content of a module is taught). Clearly a quantitative approach would be more appropriate in the last example. As with any research project, a clear research objective has to be identified to know which methods should be applied.

Types of qualitative data include:

Audio recordings and transcripts from in-depth or semi-structured interviews
Structured interview questionnaires containing substantial open comments including a substantial number of responses to open comment items.
Audio recordings and transcripts from focus group sessions.
Field notes (notes taken by the researcher while in the field [setting] being studied)
Video recordings (eg, lecture delivery, class assignments, laboratory performance)
Case study notes
Documents (reports, meeting minutes, e-mails)
Diaries, video diaries
Observation notes
Press clippings
Photographs

RIGOUR IN QUALITATIVE RESEARCH

Qualitative research is often criticized as biased, small scale, anecdotal, and/or lacking rigor; however, when it is carried out properly it is unbiased, in depth, valid, reliable, credible and rigorous. In qualitative research, there needs to be a way of assessing the “extent to which claims are supported by convincing evidence.” 1 Although the terms reliability and validity traditionally have been associated with quantitative research, increasingly they are being seen as important concepts in qualitative research as well. Examining the data for reliability and validity assesses both the objectivity and credibility of the research. Validity relates to the honesty and genuineness of the research data, while reliability relates to the reproducibility and stability of the data.

The validity of research findings refers to the extent to which the findings are an accurate representation of the phenomena they are intended to represent. The reliability of a study refers to the reproducibility of the findings. Validity can be substantiated by a number of techniques including triangulation use of contradictory evidence, respondent validation, and constant comparison. Triangulation is using 2 or more methods to study the same phenomenon. Contradictory evidence, often known as deviant cases, must be sought out, examined, and accounted for in the analysis to ensure that researcher bias does not interfere with or alter their perception of the data and any insights offered. Respondent validation, which is allowing participants to read through the data and analyses and provide feedback on the researchers' interpretations of their responses, provides researchers with a method of checking for inconsistencies, challenges the researchers' assumptions, and provides them with an opportunity to re-analyze their data. The use of constant comparison means that one piece of data (for example, an interview) is compared with previous data and not considered on its own, enabling researchers to treat the data as a whole rather than fragmenting it. Constant comparison also enables the researcher to identify emerging/unanticipated themes within the research project.

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Qualitative researchers have been criticized for overusing interviews and focus groups at the expense of other methods such as ethnography, observation, documentary analysis, case studies, and conversational analysis. Qualitative research has numerous strengths when properly conducted.

Strengths of Qualitative Research

Issues can be examined in detail and in depth.
Interviews are not restricted to specific questions and can be guided/redirected by the researcher in real time.
The research framework and direction can be quickly revised as new information emerges.
The data based on human experience that is obtained is powerful and sometimes more compelling than quantitative data.
Subtleties and complexities about the research subjects and/or topic are discovered that are often missed by more positivistic enquiries.
Data usually are collected from a few cases or individuals so findings cannot be generalized to a larger population. Findings can however be transferable to another setting.

Limitations of Qualitative Research

Research quality is heavily dependent on the individual skills of the researcher and more easily influenced by the researcher's personal biases and idiosyncrasies.
Rigor is more difficult to maintain, assess, and demonstrate.
The volume of data makes analysis and interpretation time consuming.
It is sometimes not as well understood and accepted as quantitative research within the scientific community
The researcher's presence during data gathering, which is often unavoidable in qualitative research, can affect the subjects' responses.
Issues of anonymity and confidentiality can present problems when presenting findings
Findings can be more difficult and time consuming to characterize in a visual way.

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

The following extracts are examples of how qualitative data might be presented:

Data From an Interview.

The following is an example of how to present and discuss a quote from an interview.

The researcher should select quotes that are poignant and/or most representative of the research findings. Including large portions of an interview in a research paper is not necessary and often tedious for the reader. The setting and speakers should be established in the text at the end of the quote.

The student describes how he had used deep learning in a dispensing module. He was able to draw on learning from a previous module, “I found that while using the e learning programme I was able to apply the knowledge and skills that I had gained in last year's diseases and goals of treatment module.” (interviewee 22, male)

This is an excerpt from an article on curriculum reform that used interviews 5 :

The first question was, “Without the accreditation mandate, how much of this curriculum reform would have been attempted?” According to respondents, accreditation played a significant role in prompting the broad-based curricular change, and their comments revealed a nuanced view. Most indicated that the change would likely have occurred even without the mandate from the accreditation process: “It reflects where the profession wants to be … training a professional who wants to take on more responsibility.” However, they also commented that “if it were not mandated, it could have been a very difficult road.” Or it “would have happened, but much later.” The change would more likely have been incremental, “evolutionary,” or far more limited in its scope. “Accreditation tipped the balance” was the way one person phrased it. “Nobody got serious until the accrediting body said it would no longer accredit programs that did not change.”

Data From Observations

The following example is some data taken from observation of pharmacist patient consultations using the Calgary Cambridge guide. 6 , 7 The data are first presented and a discussion follows:

Pharmacist: We will soon be starting a stop smoking clinic. Patient: Is the interview over now? Pharmacist: No this is part of it. (Laughs) You can't tell me to bog off (sic) yet. (pause) We will be starting a stop smoking service here, Patient: Yes. Pharmacist: with one-to-one and we will be able to help you or try to help you. If you want it. In this example, the pharmacist has picked up from the patient's reaction to the stop smoking clinic that she is not receptive to advice about giving up smoking at this time; in fact she would rather end the consultation. The pharmacist draws on his prior relationship with the patient and makes use of a joke to lighten the tone. He feels his message is important enough to persevere but he presents the information in a succinct and non-pressurised way. His final comment of “If you want it” is important as this makes it clear that he is not putting any pressure on the patient to take up this offer. This extract shows that some patient cues were picked up, and appropriately dealt with, but this was not the case in all examples.

Data From Focus Groups

This excerpt from a study involving 11 focus groups illustrates how findings are presented using representative quotes from focus group participants. 8

Those pharmacists who were initially familiar with CPD endorsed the model for their peers, and suggested it had made a meaningful difference in the way they viewed their own practice. In virtually all focus groups sessions, pharmacists familiar with and supportive of the CPD paradigm had worked in collaborative practice environments such as hospital pharmacy practice. For these pharmacists, the major advantage of CPD was the linking of workplace learning with continuous education. One pharmacist stated, “It's amazing how much I have to learn every day, when I work as a pharmacist. With [the learning portfolio] it helps to show how much learning we all do, every day. It's kind of satisfying to look it over and see how much you accomplish.” Within many of the learning portfolio-sharing sessions, debates emerged regarding the true value of traditional continuing education and its outcome in changing an individual's practice. While participants appreciated the opportunity for social and professional networking inherent in some forms of traditional CE, most eventually conceded that the academic value of most CE programming was limited by the lack of a systematic process for following-up and implementing new learning in the workplace. “Well it's nice to go to these [continuing education] events, but really, I don't know how useful they are. You go, you sit, you listen, but then, well I at least forget.”

The following is an extract from a focus group (conducted by the author) with first-year pharmacy students about community placements. It illustrates how focus groups provide a chance for participants to discuss issues on which they might disagree.

Interviewer: So you are saying that you would prefer health related placements? Student 1: Not exactly so long as I could be developing my communication skill. Student 2: Yes but I still think the more health related the placement is the more I'll gain from it. Student 3: I disagree because other people related skills are useful and you may learn those from taking part in a community project like building a garden. Interviewer: So would you prefer a mixture of health and non health related community placements?

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Qualitative research is becoming increasingly accepted and published in pharmacy and medical journals. Some journals and publishers have guidelines for presenting qualitative research, for example, the British Medical Journal 9 and Biomedcentral . 10 Medical Education published a useful series of articles on qualitative research. 11 Some of the important issues that should be considered by authors, reviewers and editors when publishing qualitative research are discussed below.

Introduction.

A good introduction provides a brief overview of the manuscript, including the research question and a statement justifying the research question and the reasons for using qualitative research methods. This section also should provide background information, including relevant literature from pharmacy, medicine, and other health professions, as well as literature from the field of education that addresses similar issues. Any specific educational or research terminology used in the manuscript should be defined in the introduction.

The methods section should clearly state and justify why the particular method, for example, face to face semistructured interviews, was chosen. The method should be outlined and illustrated with examples such as the interview questions, focusing exercises, observation criteria, etc. The criteria for selecting the study participants should then be explained and justified. The way in which the participants were recruited and by whom also must be stated. A brief explanation/description should be included of those who were invited to participate but chose not to. It is important to consider “fair dealing,” ie, whether the research design explicitly incorporates a wide range of different perspectives so that the viewpoint of 1 group is never presented as if it represents the sole truth about any situation. The process by which ethical and or research/institutional governance approval was obtained should be described and cited.

The study sample and the research setting should be described. Sampling differs between qualitative and quantitative studies. In quantitative survey studies, it is important to select probability samples so that statistics can be used to provide generalizations to the population from which the sample was drawn. Qualitative research necessitates having a small sample because of the detailed and intensive work required for the study. So sample sizes are not calculated using mathematical rules and probability statistics are not applied. Instead qualitative researchers should describe their sample in terms of characteristics and relevance to the wider population. Purposive sampling is common in qualitative research. Particular individuals are chosen with characteristics relevant to the study who are thought will be most informative. Purposive sampling also may be used to produce maximum variation within a sample. Participants being chosen based for example, on year of study, gender, place of work, etc. Representative samples also may be used, for example, 20 students from each of 6 schools of pharmacy. Convenience samples involve the researcher choosing those who are either most accessible or most willing to take part. This may be fine for exploratory studies; however, this form of sampling may be biased and unrepresentative of the population in question. Theoretical sampling uses insights gained from previous research to inform sample selection for a new study. The method for gaining informed consent from the participants should be described, as well as how anonymity and confidentiality of subjects were guaranteed. The method of recording, eg, audio or video recording, should be noted, along with procedures used for transcribing the data.

Data Analysis.

A description of how the data were analyzed also should be included. Was computer-aided qualitative data analysis software such as NVivo (QSR International, Cambridge, MA) used? Arrival at “data saturation” or the end of data collection should then be described and justified. A good rule when considering how much information to include is that readers should have been given enough information to be able to carry out similar research themselves.

One of the strengths of qualitative research is the recognition that data must always be understood in relation to the context of their production. 1 The analytical approach taken should be described in detail and theoretically justified in light of the research question. If the analysis was repeated by more than 1 researcher to ensure reliability or trustworthiness, this should be stated and methods of resolving any disagreements clearly described. Some researchers ask participants to check the data. If this was done, it should be fully discussed in the paper.

An adequate account of how the findings were produced should be included A description of how the themes and concepts were derived from the data also should be included. Was an inductive or deductive process used? The analysis should not be limited to just those issues that the researcher thinks are important, anticipated themes, but also consider issues that participants raised, ie, emergent themes. Qualitative researchers must be open regarding the data analysis and provide evidence of their thinking, for example, were alternative explanations for the data considered and dismissed, and if so, why were they dismissed? It also is important to present outlying or negative/deviant cases that did not fit with the central interpretation.

The interpretation should usually be grounded in interviewees or respondents' contributions and may be semi-quantified, if this is possible or appropriate, for example, “Half of the respondents said …” “The majority said …” “Three said…” Readers should be presented with data that enable them to “see what the researcher is talking about.” 1 Sufficient data should be presented to allow the reader to clearly see the relationship between the data and the interpretation of the data. Qualitative data conventionally are presented by using illustrative quotes. Quotes are “raw data” and should be compiled and analyzed, not just listed. There should be an explanation of how the quotes were chosen and how they are labeled. For example, have pseudonyms been given to each respondent or are the respondents identified using codes, and if so, how? It is important for the reader to be able to see that a range of participants have contributed to the data and that not all the quotes are drawn from 1 or 2 individuals. There is a tendency for authors to overuse quotes and for papers to be dominated by a series of long quotes with little analysis or discussion. This should be avoided.

Participants do not always state the truth and may say what they think the interviewer wishes to hear. A good qualitative researcher should not only examine what people say but also consider how they structured their responses and how they talked about the subject being discussed, for example, the person's emotions, tone, nonverbal communication, etc. If the research was triangulated with other qualitative or quantitative data, this should be discussed.

Discussion.

The findings should be presented in the context of any similar previous research and or theories. A discussion of the existing literature and how this present research contributes to the area should be included. A consideration must also be made about how transferrable the research would be to other settings. Any particular strengths and limitations of the research also should be discussed. It is common practice to include some discussion within the results section of qualitative research and follow with a concluding discussion.

The author also should reflect on their own influence on the data, including a consideration of how the researcher(s) may have introduced bias to the results. The researcher should critically examine their own influence on the design and development of the research, as well as on data collection and interpretation of the data, eg, were they an experienced teacher who researched teaching methods? If so, they should discuss how this might have influenced their interpretation of the results.

Conclusion.

The conclusion should summarize the main findings from the study and emphasize what the study adds to knowledge in the area being studied. Mays and Pope suggest the researcher ask the following 3 questions to determine whether the conclusions of a qualitative study are valid 12 : How well does this analysis explain why people behave in the way they do? How comprehensible would this explanation be to a thoughtful participant in the setting? How well does the explanation cohere with what we already know?

CHECKLIST FOR QUALITATIVE PAPERS

This paper establishes criteria for judging the quality of qualitative research. It provides guidance for authors and reviewers to prepare and review qualitative research papers for the American Journal of Pharmaceutical Education . A checklist is provided in Appendix 1 to assist both authors and reviewers of qualitative data.

ACKNOWLEDGEMENTS

Thank you to the 3 reviewers whose ideas helped me to shape this paper.

Appendix 1. Checklist for authors and reviewers of qualitative research.

Introduction

□ Research question is clearly stated.
□ Research question is justified and related to the existing knowledge base (empirical research, theory, policy).
□ Any specific research or educational terminology used later in manuscript is defined.
□ The process by which ethical and or research/institutional governance approval was obtained is described and cited.
□ Reason for choosing particular research method is stated.
□ Criteria for selecting study participants are explained and justified.
□ Recruitment methods are explicitly stated.
□ Details of who chose not to participate and why are given.
□ Study sample and research setting used are described.
□ Method for gaining informed consent from the participants is described.
□ Maintenance/Preservation of subject anonymity and confidentiality is described.
□ Method of recording data (eg, audio or video recording) and procedures for transcribing data are described.
□ Methods are outlined and examples given (eg, interview guide).
□ Decision to stop data collection is described and justified.
□ Data analysis and verification are described, including by whom they were performed.
□ Methods for identifying/extrapolating themes and concepts from the data are discussed.
□ Sufficient data are presented to allow a reader to assess whether or not the interpretation is supported by the data.
□ Outlying or negative/deviant cases that do not fit with the central interpretation are presented.
□ Transferability of research findings to other settings is discussed.
□ Findings are presented in the context of any similar previous research and social theories.
□ Discussion often is incorporated into the results in qualitative papers.
□ A discussion of the existing literature and how this present research contributes to the area is included.
□ Any particular strengths and limitations of the research are discussed.
□ Reflection of the influence of the researcher(s) on the data, including a consideration of how the researcher(s) may have introduced bias to the results is included.

Conclusions

□ The conclusion states the main finings of the study and emphasizes what the study adds to knowledge in the subject area.

Feedback in the Writing Process

Qualitative and quantitative research, learning objective.

By the end of this section, you will be able to:

Compare and contrast the feedback that can be obtained with qualitative and quantitative research.
Discuss validity, reliability, and statistical significance.

Perhaps you have heard the term “market research” or have taken a class on statistics. Whether your understanding of the gathering of credible, reliable information is emerging or developed, a general awareness of research is essential for business writing. Many businesses use research as a preproduct, postproduct, and service development method of obtaining feedback. Understanding the feedback from research can influence your writing as you learn more about your target audience. Ralph Rosnow and Robert Rosenthal offer a solid introductory discussion into basic research terms in their text Beginning Behavioral Research: A Conceptual Primer that serves our discussion well. Rosnow, R., & Rosenthal, R. (1999). Beginning behavioral research: A conceptual primer (3rd ed.). Englewood Cliffs, NJ: Prentice Hall.

We can divide research into two basic categories:

Qualitative research focuses on quality in the sense of “what is it like?” or “how does it feel?”
Quantitative research focuses on quantity in the sense of “how many customers?” or “what percentage?”

Let’s examine the advantages and disadvantages of each of these kinds of research.

Obtaining Feedback with Qualitative Research

Qualitative research involves investigative methods that cross subjects and academic disciplines to gain in-depth information. If quantitive research explores “what,” qualitative research explores “how” and “why.” From interviews to focus groups, many of the face-to-face strategies used to gather information are qualitative in nature.

You have five senses, and you may be able to distinguish between sweet and salty foods, but can you describe what you taste and smell? Let’s say you work for a vineyard, and have been tasked to write a paragraph describing a new wine. Could you? Capturing fine data points and representing them in words and symbols can be a significant challenge for researchers. When testing the wine with a focus group, you might want information on how it is perceived, and the responses may be varied and unusual. What do you do with the information you gather? You may be able to identify trends among the varied responses, and create groups that indicate a woody or earthy flavor, but numbers will fail to capture the nuances of flavor and body of the wines in the information.

Some information—like the way consumers characterize the taste of a wine—is a challenge to obtain, and qualitative research often serves well in this capacity. If quantitative research handles large audiences well, qualitative research allows for in-depth interpersonal interviews that produce rich and meaningful results. The information may not be as reliable, and your ability to produce the same results over time may be limited, but humans are emotional, irrational, and unpredictable. They are also, each in his or her own way, unique. As you increase the level of perspective in terms of abstraction, all humans may eventually come to look similar, even the same. We all possess some similar characteristics, such as the use of language, or the composition of our bodies. But when you look more closely, you see the diverse range of languages, and learn that not everyone has 206 bones in an adult body. Between these two views we find the range of information that quantitative and qualitative research attempt to address.

Suppose we want to determine who has greater lifetime risk of developing heart disease, a man or a woman? If we are talking about an individual man and an individual woman, our answer might be quite different from what it would be if we were talking about men in general versus women in general. A survey may work well to capture the data about men versus women, but a face-to-face interview with a man and a woman will allow for interaction, follow-up questions, and a much better picture of the question: between this individual woman and this individual man, who is more likely to be at risk? The risk and protective factors we learn from broad research projects involving thousands of subjects have value, but there are times when a broad brushstroke will fail to capture the fine data that is needed or desired.

Imagine that you are involved with a direct observation of buying behavior by reviewing video recordings of security cameras that clearly show your company’s product in relation to other products on the shelf. You may find, particularly after a review of the literature, that product placement makes a significant impact on purchase decisions. In addition, you may be involved with some level of participation in the setting. Serving as a participant observer means you are part of the process, involved in action, and not separated from the interaction. You look at the sales experience through the eyes of a participant, and view others through the eyes of an observer. You may find that interviews and focus groups serve to teach you more about your audience, but may also find that others have conducted similar interviews and learn from their findings.

As a business writer, you should be familiar with qualitative research and its relative strengths and weaknesses. You may use some of its techniques to gather information about your audience, may cite research that involves qualitative methods, and may utilize its strategies with an audience post document, product, or service.

Obtaining Feedback with Quantitative Research

Quantitative research involves investigation and analysis of data and relationships between data that can be represented by numbers. It is often used to test a hypothesis, and normally involves large volumes of data. Where a qualitative research project may involve a dozen interviews, a quantitative one would involve hundreds or thousands. Since each interview carries a cost—and a thousand or ten thousand interviews may exceed the research budget of your organization—a more cost-effective alternative must be found. By limiting the number of questions and limiting the ways in which participants can respond, the data can be gathered at a lower cost with often a higher level of statistical validity.

In qualitative research, you may ask an open-ended question like “What does the wine taste like?” In quantitative research, you may limit the response options: “Does the wine taste (a) woody, (b) fruity, or (c) both?” You may find that 90 percent of respondents indicate answer (c); you can represent it with numbers and a graph, but it may not serve your investigation the way you planned.

Research methodologies involve examining and evaluating the methods used in investigation or soliciting feedback. They are used to address and improve poorly worded questions, and to help the investigator match the research goal to the method. Quantitative research serves us well when we ask, does vitamin C, taken at a dosage of 500 mg daily for five years, lower the incidence of the common cold? We could track a thousand participants in the study who provide intake prescreening information, confirm daily compliance, and participate in periodic interviews. We also know that part of our group is taking a placebo (sugar pill) as part of the requirements of a double-blind study. At the end of the term, we have certain numbers that may be able to indicate the degree to which vitamin C affects the incidence rate of illness.

Advertisers often conduct research to learn more about preference and attitudes, two areas that are not easily captured. Sometimes preference studies use Likert scales, which give respondents a preset scale to rate their answers. An example of a Likert item might be, “Please indicate to what degree you agree or disagree with this statement: I enjoy drinking brand X wine. Do you (1) strongly agree, (2) agree, (3) neither agree nor disagree, (4) disagree, or (5) strongly disagree?”

There is a tendency for some attitudinal and preferential research that may be more accurately described as qualitative, to be described in numerical terms. For example, you have probably heard the claim that “four out of five dentists prefer brand X,” when in itself, the number or representation of preference is meaningless. As an astute business writer, you will be able to understand pre (before) and post (after) document, product, or service research investigations and distinguish between the two main approaches.

What Is Validity?

How do you know the results presented in a study or article have value? How do you know they are valid? Validity involves the strength of conclusions, inferences or assertions. Thomas Cook and Dan Campbell Cook, T. D., & Campbel, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings . Chicago, IL: Rand McNally. indicate that validity is often the best available approximation of the truth or falseness of an inference, proposition, or conclusion. Readers want to know that your information has value and that there is confidence in its points, supporting information, and conclusions. They want to know you are right and not making false statements.

One way you can address the value of validity is to cite all your sources clearly. As a writer, you may certainly include information from authorities in the field when the attribution is relevant and the citation is clear. Giving credit where credit is due is one way to make your information more valuable, and by referencing the sources clearly, you enable the reader to assess the validity of the information you have provided.

Does all feedback have validity? Just as there are many threats to validity in research applications, you cannot always be sure that the feedback you receive is accurate or truthful. Have students ever evaluated professors negatively because of the required work in the course? Of course. In the same way, some readers may have issues with the topic or your organization. Their feedback post may be less than supportive, and even openly hostile. Assess the validity of the feedback, respond with professionalism at all times, and learn how to let go of the negative messages that offer little opportunity to improve understanding.

What Is Reliability?

Reliability is the consistency of your measurements. The degree to which an instrument gives the same measurement each and every time with the same subjects, in the same context, is a measure of its reliability. For example, if you took your temperature three times within fifteen minutes, and your thermometer gave a different reading each time—say, 98.6, 96.6, and 100.2—you would conclude that your thermometer was unreliable.

How does this apply to feedback in business writing? Let’s say you have three sales agents who will complete follow-up interactions with three customers after you have sent a report to each customer on their purchases to date with suggestions for additional products and services. All three sales agents have the same information about the products and services, but will they perform the same? Of course not. Each one, even if they are trained to stay on script and follow specific protocols, will not be identical in their approach and delivery. Each customer is also different, so the context is different in each case. As business professionals, we need to learn about our environment and adapt to it. This requires feedback and attention to the information in many forms. We need to assess the degree of strength or weakness of the information, its reliability, or validity, and be prepared to act on that information. Successful businesses, and by extension successful business communicators, recognize that communication is a two-way process in which we need to listen, learn, and respond to feedback. We need to meet and exceed the expectations of our customers.

Inter-rater reliability involves the degree to which each evaluator evaluates the same in similar contexts. One can think of a college essay, for example, to better understand this concept. Let’s say you write an essay on customer relationship management and submit it to the instructor of your business communication class. At the same time, you submit the same essay to your English professor, and you submit a copy to your marketing professor. Will all three professors evaluate your essay the same? Of course not. They will each have their own set of expectations and respective disciplines that will influence what they value and how the evaluate. Still, if your essay is thoroughly researched, logically organized, and carefully written, each professor may give it a better than average grade. If this is the case, inter-rater reliability would indicate that you did a good job on the essay.

What Is Statistically Significant?

This is a research term that is often used and commonly misunderstood. Not every research finding is statistically significant, and many of those that are considered significant are only slightly more likely than pure chance. Statistically significant findings are those that have a high level of reliability, in that if the same test is applied in the same context to the same subjects, the results will come out the same time and time again. Stone-Romero, E. F. (2002). The relative validity and usefulness of various empirical research designs. In S. G. Rogelberg (Ed.), Handbook of research methods in industrial and organizational psycology (pp. 77–98). Malden, MA: Blackwell. You may see a confidence level of +/– (plus or minus) three percentage points as a common statement of reliability and confidence in a poll. It means that if the poll were repeated, there is confidence that the results would be within three points above or below the percentages in the original results. When statements of statistical significance are made, you will know that it means a difference or a relationship was established with confidence by the study. That confidence gives the results credibility.

KEY TAKEAWAY

Visit the Web site of a major polling organization such as Gallup, Pew, Roper, or Zogby. What can you learn about how the organization conducts polls? How valid, reliable, and statistically significant are the results of this organization’s polls, and how do you know? Discuss your findings with your classmates.
Find an example where information is presented to support a claim, but you perceive it to be less than valid or reliable. Share your observations and review the results of your classmates’ similar efforts.
Communication For Business Success. Authored by : anonymous. Located at : http://2012books.lardbucket.org/books/communication-for-business-success/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

[Guide] How to Present Qualitative Research Findings in PowerPoint?

By: Author Shrot Katewa

As a researcher, it is quite pointless to do the research if we are unable to share the findings with our audience appropriately! Using PowerPoint is one of the best ways to present research outcomes. But, how does one present qualitative research findings using PowerPoint?

In order to present the qualitative research findings using PowerPoint, you need to create a robust structure for your presentation, make it engaging and visually appealing, present the patterns with explanations for it and highlight the conclusion of your research findings.

In this article, we will help you understand the structure of your presentation. Plus, we’ll share some handy tips that will make your qualitative research presentation really effective!

How to Create a Structure for your Qualitative Research Presentation?

Creating the right structure for your presentation is key to ensuring that it is correctly understood by your audience.

The structure of your Research Presentation not only makes it easier for you to create the document, it also makes it simple for the audience to understand what all will be covered in the presentation at the time of presenting it to your audience.

Furthermore, having a robust structure is a great way to ensure that you don’t miss out on any of the points while working on creating the presentation.

But, what structure should one follow?

Creating a good structure can be tricky for some. Thus, I’m sharing what has worked well for me during my previous research projects.

NOTE – It is important to note that although the following structure is highly effective for most research findings presentation, it has been generalized in order to serve a wide range of research projects. You may want to take a look at points that are very specific to the nature of your research project and include them at your discretion.

Here’s my recommended structure to create your Research Findings presentation –

1. Objective of the Research

A great way to start your presentation is to highlight the objective of your research project.

It is important to remember that merely sharing the objective may sometimes not be enough. A short backstory along with the purpose of your research project can pack a powerful punch ! It not only validates the reasoning for your project but also subtly establishes trust with your audience.

However, do make sure that you’re not reading the backstory from the slide. Let it flow naturally when you are delivering the presentation. Keep the presentation as minimalistic as possible.

2. Key Parameters Considered for Measurement

Once you’ve established the objective, the next thing that you may want to do is perhaps share the key parameters considered for the success of your project.

Every research project, including qualitative research, needs to have a few key parameters to measure against the objective of the research.

For example – If the goal of your project is to gather the sentiments of a certain group of people for a particular product, you may need to measure their feelings. Are they happy or unhappy using the product? How do they perceive the branding of the product? Is it affordable?

Make sure that you list down all such key parameters that were considered while conducting the qualitative research.

In general, laying these out before sharing the outcome can help your audience think from your perspective and look at the findings from the correct lens.

3. Research Methodology Adopted

The next thing that you may want to include in your presentation is the methodology that you adopted for conducting the research.

By knowing your approach, the audience can be better prepared for the outcome of your project. Ensure that you provide sound reasoning for the chosen methodology.

This section of your presentation can also showcase some pictures of the research being conducted. If you have captured a video, include that. Doing this provides further validation of your project.

4. Research Outcomes (Presenting Descriptive Analysis)

This is the section that will constitute the bulk of the your presentation.

Use the slides in this section to describe the observations, and the resulting outcomes on each of the key parameters that were considered for the research project.

It is usually a good idea to dedicate at least 1 or more slides for each parameter . Make sure that you present data wherever possible. However, ensure that the data presented can be easily comprehended.

Provide key learnings from the data, highlight any outliers, and possible reasoning for it. Try not to go too in-depth with the stats as this can overwhelm the audience. Remember, a presentation is most helpful when it is used to provide key highlights of the research !

Apart from using the data, make sure that you also include a few quotes from the participants.

5. Summary and Learnings from the Research

Once you’ve taken the audience through the core part of your research findings, it is a good practice to summarize the key learnings from each of the section of your project.

Make sure your touch upon some of the key learnings covered in the research outcome of your presentation.

Furthermore, include any additional observations and key points that you may have had which were previously not covered.

The summary slide also often acts as “Key Takeaways” from the research for your audience. Thus, make sure that you maintain brevity and highlight only the points that you want your audience to remember even after the presentation.

6. Inclusions and Exclusions (if any)

While this can be an optional section for some of the researchers.

However, dedicating a section on inclusions and exclusions in your presentation can be a great value add! This section helps your audience understand the key factors that were excluded (or included) on purpose!

Moreover, it creates a sense of thoroughness in the minds of your audience.

7. Conclusion of the Research

The purpose of the conclusion slide of your research findings presentation is to revisit the objective, and present a conclusion.

A conclusion may simply validate or nullify the objective. It may sometimes do neither. Nevertheless, having a conclusion slide makes your presentation come a full circle. It creates this sense of completion in the minds of your audience.

8. Questions

Finally, since your audience did not spend as much time as you did on the research project, people are bound to have a few questions.

Thus, the last part of your presentation structure should be dedicated to allowing your audience to ask questions.

Tips for Effectively Presenting Qualitative Research Findings using PowerPoint

For a presentation to be effective, it is important that the presentation is not only well structured but also that it is well created and nicely delivered!

While we have already covered the structure, let me share with you some tips that you can help you create and deliver the presentation effectively.

Tip 1 – Use Visuals

Using visuals in your presentation is a great way to keep the presentations engaging!

Visual aids not only help make the presentation less boring, but it also helps your audience in retaining the information better!

So, use images and videos of the actual research wherever possible. If these do not suffice or do not give a professional feel, there are a number of resources online from where you can source royalty-free images.

My recommendation for high-quality royalty-free images would be either Unsplash or Pexels . Both are really good. The only downside is that they often do not provide the perfect image that can be used. That said, it can get the job done for at least half the time.

If you are unable to find the perfect free image, I recommend checking out Dreamstime . They have a huge library of images and are much cheaper than most of the other image banks. I personally use Dreamstime for my presentation projects!

Tip 2 – Tell a Story (Don’t Show Just Data!)

I cannot stress enough on how important it is to give your presentation a human touch. Delivering a presentation in the form of a story does just that! Furthermore, storytelling is also a great tool for visualization .

Data can be hard-hitting, whereas a touching story can tickle the emotions of your audience on various levels!

One of the best ways to present a story with your research project is to start with the backstory of the objective. We’ve already talked about this in the earlier part of this article.

Start with why is this research project is so important. Follow a story arc that provides an exciting experience of the beginning, the middle, and a progression towards a climax; much like a plot of a soap opera.

Tip 3 – Include Quotes of the Participants

Including quotes of the participants in your research findings presentation not only provides evidence but also demonstrates authenticity!

Quotes function as a platform to include the voice of the target group and provide a peek into the mindset of the target audience.

When using quotes, keep these things in mind –

1. Use Quotes in their Unedited Form

When using quotes in your presentation, make sure that you use them in their raw unedited form.

The need to edit quotes should be only restricted to aid comprehension and sometimes coherence.

Furthermore, when editing the quotes, make sure that you use brackets to insert clarifying words. The standard format for using the brackets is to use square brackets for clarifying words and normal brackets for adding a missing explanation.

2. How to Decide which Quotes to Consider?

It is important to know which quotes to include in your presentation. I use the following 3 criteria when selecting the quote –

Relevance – Consider the quotes that are relevant, and trying to convey the point that you want to establish.
Length – an ideal quote should be not more than 1-2 sentences long.
Choose quotes that are well-expressed and striking in nature.

3. Preserve Identity of the Participant

It is important to preserve and protect the identity of the participant. This can be done by maintaining confidentiality and anonymity.

Thus, refrain from using the name of the participant. An alternative could be using codes, using pseudonyms (made up names) or simply using other general non-identifiable parameters.

Do note, when using pseudonyms, remember to highlight it in the presentation.

If, however, you do need to use the name of the respondent, make sure that the participant is okay with it and you have adequate permissions to use their name.

Tip 4 – Make your Presentation Visually Appealing and Engaging

It is quite obvious for most of us that we need to create a visually appealing presentation. But, making it pleasing to the eye can be a bit challenging.

Fortunately, we wrote a detailed blog post with tips on how to make your presentation attractive. It provides you with easy and effective tips that you can use even as a beginner! Make sure you check that article.

7 EASY tips that ALWAYS make your PPT presentation attractive (even for beginners)

In addition to the tips mentioned in the article, let me share a few things that you can do which are specific to research outcome presentations.

4.1 Use a Simple Color Scheme

Using the right colors are key to make a presentation look good.

One of the most common mistakes that people make is use too many colors in their presentation!

My recommendation would be to go with a monochromatic color scheme in PowerPoint .

4.2 Make the Data Tables Simple and Visually Appealing

When making a presentation on research outcomes, you are bound to present some data.

But, when data is not presented in a proper manner, it can easily and quickly make your presentation look displeasing! The video below can be a good starting point.

Using neat looking tables can simply transform the way your presentation looks. So don’t just dump the data from excel on your PowerPoint presentation. Spend a few minutes on fixing it!

4.3 Use Graphs and Charts (wherever necessary)

When presenting data, my recommendation would be that graphs and charts should be your first preference.

Using graphs or charts make it easier to read the data, takes less time for the audience to comprehend, and it also helps to identify a trend.

However, make sure that the correct chart type is used when representing the data. The last thing that you want is to poorly represent a key piece of information.

4.4 Use Icons instead of Bullet Points

Consider the following example –

This slide could have been created just as easily using bullet points. However, using icons and representing the information in a different format makes the slide pleasing on the eye.

Thus, always try to use icons wherever possible instead of bullet points.

Tip 5 – Include the Outliers

Many times, as a research project manager, we tend to focus on the trends extracted from a data set.

While it is important to identify patterns in the data and provide an adequate explanation for the pattern, it is equally important sometimes to highlight the outliers prominently.

It is easy to forget that there may be hidden learnings even in the outliers. At times, the data trend may be re-iterating the common wisdom. However, upon analyzing the outlier data points, you may get insight into how a few participants are doing things successfully despite not following the common knowledge.

That said, not every outlier will reveal hidden information. So, do verify what to include and what to exclude.

Tip 6 – Take Inspiration from other Presentations

I admit, making any presentation can be a tough ask let alone making a presentation for showcasing qualitative research findings. This is especially hard when we don’t have the necessary skills for creating a presentation.

One quick way to overcome this challenge could be take inspiration from other similar presentations that we may have liked.

There is no shame in being inspired from others. If you don’t have any handy references, you can surely Google it to find a few examples.

One trick that almost always works for me is using Pinterest .

But, don’t just directly search for a research presentation. You will have little to no success with it. The key is to look for specific examples for inspiration. For eg. search for Title Slide examples, or Image Layout Examples in Presentation.

Tip 7 – Ask Others to Critic your Presentation

The last tip that I would want to provide is to make sure that you share the presentation with supportive colleagues or mentors to attain feedback.

This step can be critical to iron out the chinks in the armor. As research project manager, it is common for you to get a bit too involved with the project. This can lead to possibilities wherein you miss out on things.

A good way to overcome this challenge is to get a fresh perspective on your project and the presentation once it has been prepared.

Taking critical feedback before your final presentation can also prepare you to handle tough questions in an adept manner.

Final Thoughts

It is quite important to ensure that we get it right when working on a presentation that showcases the findings of our research project. After all, we don’t want to be in a situation wherein we put in all the hard-work in the project, but we fail to deliver the outcome appropriately.

I hope you will find the aforementioned tips and structure useful, and if you do, make sure that you bookmark this page and spread the word. Wishing you all the very best for your project!

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Qualitative Data Analysis

23 Presenting the Results of Qualitative Analysis

Mikaila Mariel Lemonik Arthur

Qualitative research is not finished just because you have determined the main findings or conclusions of your study. Indeed, disseminating the results is an essential part of the research process. By sharing your results with others, whether in written form as scholarly paper or an applied report or in some alternative format like an oral presentation, an infographic, or a video, you ensure that your findings become part of the ongoing conversation of scholarship in your field, forming part of the foundation for future researchers. This chapter provides an introduction to writing about qualitative research findings. It will outline how writing continues to contribute to the analysis process, what concerns researchers should keep in mind as they draft their presentations of findings, and how best to organize qualitative research writing

As you move through the research process, it is essential to keep yourself organized. Organizing your data, memos, and notes aids both the analytical and the writing processes. Whether you use electronic or physical, real-world filing and organizational systems, these systems help make sense of the mountains of data you have and assure you focus your attention on the themes and ideas you have determined are important (Warren and Karner 2015). Be sure that you have kept detailed notes on all of the decisions you have made and procedures you have followed in carrying out research design, data collection, and analysis, as these will guide your ultimate write-up.

First and foremost, researchers should keep in mind that writing is in fact a form of thinking. Writing is an excellent way to discover ideas and arguments and to further develop an analysis. As you write, more ideas will occur to you, things that were previously confusing will start to make sense, and arguments will take a clear shape rather than being amorphous and poorly-organized. However, writing-as-thinking cannot be the final version that you share with others. Good-quality writing does not display the workings of your thought process. It is reorganized and revised (more on that later) to present the data and arguments important in a particular piece. And revision is totally normal! No one expects the first draft of a piece of writing to be ready for prime time. So write rough drafts and memos and notes to yourself and use them to think, and then revise them until the piece is the way you want it to be for sharing.

Bergin (2018) lays out a set of key concerns for appropriate writing about research. First, present your results accurately, without exaggerating or misrepresenting. It is very easy to overstate your findings by accident if you are enthusiastic about what you have found, so it is important to take care and use appropriate cautions about the limitations of the research. You also need to work to ensure that you communicate your findings in a way people can understand, using clear and appropriate language that is adjusted to the level of those you are communicating with. And you must be clear and transparent about the methodological strategies employed in the research. Remember, the goal is, as much as possible, to describe your research in a way that would permit others to replicate the study. There are a variety of other concerns and decision points that qualitative researchers must keep in mind, including the extent to which to include quantification in their presentation of results, ethics, considerations of audience and voice, and how to bring the richness of qualitative data to life.

Quantification, as you have learned, refers to the process of turning data into numbers. It can indeed be very useful to count and tabulate quantitative data drawn from qualitative research. For instance, if you were doing a study of dual-earner households and wanted to know how many had an equal division of household labor and how many did not, you might want to count those numbers up and include them as part of the final write-up. However, researchers need to take care when they are writing about quantified qualitative data. Qualitative data is not as generalizable as quantitative data, so quantification can be very misleading. Thus, qualitative researchers should strive to use raw numbers instead of the percentages that are more appropriate for quantitative research. Writing, for instance, “15 of the 20 people I interviewed prefer pancakes to waffles” is a simple description of the data; writing “75% of people prefer pancakes” suggests a generalizable claim that is not likely supported by the data. Note that mixing numbers with qualitative data is really a type of mixed-methods approach. Mixed-methods approaches are good, but sometimes they seduce researchers into focusing on the persuasive power of numbers and tables rather than capitalizing on the inherent richness of their qualitative data.

A variety of issues of scholarly ethics and research integrity are raised by the writing process. Some of these are unique to qualitative research, while others are more universal concerns for all academic and professional writing. For example, it is essential to avoid plagiarism and misuse of sources. All quotations that appear in a text must be properly cited, whether with in-text and bibliographic citations to the source or with an attribution to the research participant (or the participant’s pseudonym or description in order to protect confidentiality) who said those words. Where writers will paraphrase a text or a participant’s words, they need to make sure that the paraphrase they develop accurately reflects the meaning of the original words. Thus, some scholars suggest that participants should have the opportunity to read (or to have read to them, if they cannot read the text themselves) all sections of the text in which they, their words, or their ideas are presented to ensure accuracy and enable participants to maintain control over their lives.

Audience and Voice

When writing, researchers must consider their audience(s) and the effects they want their writing to have on these audiences. The designated audience will dictate the voice used in the writing, or the individual style and personality of a piece of text. Keep in mind that the potential audience for qualitative research is often much more diverse than that for quantitative research because of the accessibility of the data and the extent to which the writing can be accessible and interesting. Yet individual pieces of writing are typically pitched to a more specific subset of the audience.

Let us consider one potential research study, an ethnography involving participant-observation of the same children both when they are at daycare facility and when they are at home with their families to try to understand how daycare might impact behavior and social development. The findings of this study might be of interest to a wide variety of potential audiences: academic peers, whether at your own academic institution, in your broader discipline, or multidisciplinary; people responsible for creating laws and policies; practitioners who run or teach at day care centers; and the general public, including both people who are interested in child development more generally and those who are themselves parents making decisions about child care for their own children. And the way you write for each of these audiences will be somewhat different. Take a moment and think through what some of these differences might look like.

If you are writing to academic audiences, using specialized academic language and working within the typical constraints of scholarly genres, as will be discussed below, can be an important part of convincing others that your work is legitimate and should be taken seriously. Your writing will be formal. Even if you are writing for students and faculty you already know—your classmates, for instance—you are often asked to imitate the style of academic writing that is used in publications, as this is part of learning to become part of the scholarly conversation. When speaking to academic audiences outside your discipline, you may need to be more careful about jargon and specialized language, as disciplines do not always share the same key terms. For instance, in sociology, scholars use the term diffusion to refer to the way new ideas or practices spread from organization to organization. In the field of international relations, scholars often used the term cascade to refer to the way ideas or practices spread from nation to nation. These terms are describing what is fundamentally the same concept, but they are different terms—and a scholar from one field might have no idea what a scholar from a different field is talking about! Therefore, while the formality and academic structure of the text would stay the same, a writer with a multidisciplinary audience might need to pay more attention to defining their terms in the body of the text.

It is not only other academic scholars who expect to see formal writing. Policymakers tend to expect formality when ideas are presented to them, as well. However, the content and style of the writing will be different. Much less academic jargon should be used, and the most important findings and policy implications should be emphasized right from the start rather than initially focusing on prior literature and theoretical models as you might for an academic audience. Long discussions of research methods should also be minimized. Similarly, when you write for practitioners, the findings and implications for practice should be highlighted. The reading level of the text will vary depending on the typical background of the practitioners to whom you are writing—you can make very different assumptions about the general knowledge and reading abilities of a group of hospital medical directors with MDs than you can about a group of case workers who have a post-high-school certificate. Consider the primary language of your audience as well. The fact that someone can get by in spoken English does not mean they have the vocabulary or English reading skills to digest a complex report. But the fact that someone’s vocabulary is limited says little about their intellectual abilities, so try your best to convey the important complexity of the ideas and findings from your research without dumbing them down—even if you must limit your vocabulary usage.

When writing for the general public, you will want to move even further towards emphasizing key findings and policy implications, but you also want to draw on the most interesting aspects of your data. General readers will read sociological texts that are rich with ethnographic or other kinds of detail—it is almost like reality television on a page! And this is a contrast to busy policymakers and practitioners, who probably want to learn the main findings as quickly as possible so they can go about their busy lives. But also keep in mind that there is a wide variation in reading levels. Journalists at publications pegged to the general public are often advised to write at about a tenth-grade reading level, which would leave most of the specialized terminology we develop in our research fields out of reach. If you want to be accessible to even more people, your vocabulary must be even more limited. The excellent exercise of trying to write using the 1,000 most common English words, available at the Up-Goer Five website ( https://www.splasho.com/upgoer5/ ) does a good job of illustrating this challenge (Sanderson n.d.).

Another element of voice is whether to write in the first person. While many students are instructed to avoid the use of the first person in academic writing, this advice needs to be taken with a grain of salt. There are indeed many contexts in which the first person is best avoided, at least as long as writers can find ways to build strong, comprehensible sentences without its use, including most quantitative research writing. However, if the alternative to using the first person is crafting a sentence like “it is proposed that the researcher will conduct interviews,” it is preferable to write “I propose to conduct interviews.” In qualitative research, in fact, the use of the first person is far more common. This is because the researcher is central to the research project. Qualitative researchers can themselves be understood as research instruments, and thus eliminating the use of the first person in writing is in a sense eliminating information about the conduct of the researchers themselves.

But the question really extends beyond the issue of first-person or third-person. Qualitative researchers have choices about how and whether to foreground themselves in their writing, not just in terms of using the first person, but also in terms of whether to emphasize their own subjectivity and reflexivity, their impressions and ideas, and their role in the setting. In contrast, conventional quantitative research in the positivist tradition really tries to eliminate the author from the study—which indeed is exactly why typical quantitative research avoids the use of the first person. Keep in mind that emphasizing researchers’ roles and reflexivity and using the first person does not mean crafting articles that provide overwhelming detail about the author’s thoughts and practices. Readers do not need to hear, and should not be told, which database you used to search for journal articles, how many hours you spent transcribing, or whether the research process was stressful—save these things for the memos you write to yourself. Rather, readers need to hear how you interacted with research participants, how your standpoint may have shaped the findings, and what analytical procedures you carried out.

Making Data Come Alive

One of the most important parts of writing about qualitative research is presenting the data in a way that makes its richness and value accessible to readers. As the discussion of analysis in the prior chapter suggests, there are a variety of ways to do this. Researchers may select key quotes or images to illustrate points, write up specific case studies that exemplify their argument, or develop vignettes (little stories) that illustrate ideas and themes, all drawing directly on the research data. Researchers can also write more lengthy summaries, narratives, and thick descriptions.

Nearly all qualitative work includes quotes from research participants or documents to some extent, though ethnographic work may focus more on thick description than on relaying participants’ own words. When quotes are presented, they must be explained and interpreted—they cannot stand on their own. This is one of the ways in which qualitative research can be distinguished from journalism. Journalism presents what happened, but social science needs to present the “why,” and the why is best explained by the researcher.

So how do authors go about integrating quotes into their written work? Julie Posselt (2017), a sociologist who studies graduate education, provides a set of instructions. First of all, authors need to remain focused on the core questions of their research, and avoid getting distracted by quotes that are interesting or attention-grabbing but not so relevant to the research question. Selecting the right quotes, those that illustrate the ideas and arguments of the paper, is an important part of the writing process. Second, not all quotes should be the same length (just like not all sentences or paragraphs in a paper should be the same length). Include some quotes that are just phrases, others that are a sentence or so, and others that are longer. We call longer quotes, generally those more than about three lines long, block quotes , and they are typically indented on both sides to set them off from the surrounding text. For all quotes, be sure to summarize what the quote should be telling or showing the reader, connect this quote to other quotes that are similar or different, and provide transitions in the discussion to move from quote to quote and from topic to topic. Especially for longer quotes, it is helpful to do some of this writing before the quote to preview what is coming and other writing after the quote to make clear what readers should have come to understand. Remember, it is always the author’s job to interpret the data. Presenting excerpts of the data, like quotes, in a form the reader can access does not minimize the importance of this job. Be sure that you are explaining the meaning of the data you present.

A few more notes about writing with quotes: avoid patchwriting, whether in your literature review or the section of your paper in which quotes from respondents are presented. Patchwriting is a writing practice wherein the author lightly paraphrases original texts but stays so close to those texts that there is little the author has added. Sometimes, this even takes the form of presenting a series of quotes, properly documented, with nothing much in the way of text generated by the author. A patchwriting approach does not build the scholarly conversation forward, as it does not represent any kind of new contribution on the part of the author. It is of course fine to paraphrase quotes, as long as the meaning is not changed. But if you use direct quotes, do not edit the text of the quotes unless how you edit them does not change the meaning and you have made clear through the use of ellipses (…) and brackets ([])what kinds of edits have been made. For example, consider this exchange from Matthew Desmond’s (2012:1317) research on evictions:

The thing was, I wasn’t never gonna let Crystal come and stay with me from the get go. I just told her that to throw her off. And she wasn’t fittin’ to come stay with me with no money…No. Nope. You might as well stay in that shelter.

A paraphrase of this exchange might read “She said that she was going to let Crystal stay with her if Crystal did not have any money.” Paraphrases like that are fine. What is not fine is rewording the statement but treating it like a quote, for instance writing:

The thing was, I was not going to let Crystal come and stay with me from beginning. I just told her that to throw her off. And it was not proper for her to come stay with me without any money…No. Nope. You might as well stay in that shelter.

But as you can see, the change in language and style removes some of the distinct meaning of the original quote. Instead, writers should leave as much of the original language as possible. If some text in the middle of the quote needs to be removed, as in this example, ellipses are used to show that this has occurred. And if a word needs to be added to clarify, it is placed in square brackets to show that it was not part of the original quote.

Data can also be presented through the use of data displays like tables, charts, graphs, diagrams, and infographics created for publication or presentation, as well as through the use of visual material collected during the research process. Note that if visuals are used, the author must have the legal right to use them. Photographs or diagrams created by the author themselves—or by research participants who have signed consent forms for their work to be used, are fine. But photographs, and sometimes even excerpts from archival documents, may be owned by others from whom researchers must get permission in order to use them.

A large percentage of qualitative research does not include any data displays or visualizations. Therefore, researchers should carefully consider whether the use of data displays will help the reader understand the data. One of the most common types of data displays used by qualitative researchers are simple tables. These might include tables summarizing key data about cases included in the study; tables laying out the characteristics of different taxonomic elements or types developed as part of the analysis; tables counting the incidence of various elements; and 2×2 tables (two columns and two rows) illuminating a theory. Basic network or process diagrams are also commonly included. If data displays are used, it is essential that researchers include context and analysis alongside data displays rather than letting them stand by themselves, and it is preferable to continue to present excerpts and examples from the data rather than just relying on summaries in the tables.

If you will be using graphs, infographics, or other data visualizations, it is important that you attend to making them useful and accurate (Bergin 2018). Think about the viewer or user as your audience and ensure the data visualizations will be comprehensible. You may need to include more detail or labels than you might think. Ensure that data visualizations are laid out and labeled clearly and that you make visual choices that enhance viewers’ ability to understand the points you intend to communicate using the visual in question. Finally, given the ease with which it is possible to design visuals that are deceptive or misleading, it is essential to make ethical and responsible choices in the construction of visualization so that viewers will interpret them in accurate ways.

The Genre of Research Writing

As discussed above, the style and format in which results are presented depends on the audience they are intended for. These differences in styles and format are part of the genre of writing. Genre is a term referring to the rules of a specific form of creative or productive work. Thus, the academic journal article—and student papers based on this form—is one genre. A report or policy paper is another. The discussion below will focus on the academic journal article, but note that reports and policy papers follow somewhat different formats. They might begin with an executive summary of one or a few pages, include minimal background, focus on key findings, and conclude with policy implications, shifting methods and details about the data to an appendix. But both academic journal articles and policy papers share some things in common, for instance the necessity for clear writing, a well-organized structure, and the use of headings.

So what factors make up the genre of the academic journal article in sociology? While there is some flexibility, particularly for ethnographic work, academic journal articles tend to follow a fairly standard format. They begin with a “title page” that includes the article title (often witty and involving scholarly inside jokes, but more importantly clearly describing the content of the article); the authors’ names and institutional affiliations, an abstract , and sometimes keywords designed to help others find the article in databases. An abstract is a short summary of the article that appears both at the very beginning of the article and in search databases. Abstracts are designed to aid readers by giving them the opportunity to learn enough about an article that they can determine whether it is worth their time to read the complete text. They are written about the article, and thus not in the first person, and clearly summarize the research question, methodological approach, main findings, and often the implications of the research.

After the abstract comes an “introduction” of a page or two that details the research question, why it matters, and what approach the paper will take. This is followed by a literature review of about a quarter to a third the length of the entire paper. The literature review is often divided, with headings, into topical subsections, and is designed to provide a clear, thorough overview of the prior research literature on which a paper has built—including prior literature the new paper contradicts. At the end of the literature review it should be made clear what researchers know about the research topic and question, what they do not know, and what this new paper aims to do to address what is not known.

The next major section of the paper is the section that describes research design, data collection, and data analysis, often referred to as “research methods” or “methodology.” This section is an essential part of any written or oral presentation of your research. Here, you tell your readers or listeners “how you collected and interpreted your data” (Taylor, Bogdan, and DeVault 2016:215). Taylor, Bogdan, and DeVault suggest that the discussion of your research methods include the following:

The particular approach to data collection used in the study;
Any theoretical perspective(s) that shaped your data collection and analytical approach;
When the study occurred, over how long, and where (concealing identifiable details as needed);
A description of the setting and participants, including sampling and selection criteria (if an interview-based study, the number of participants should be clearly stated);
The researcher’s perspective in carrying out the study, including relevant elements of their identity and standpoint, as well as their role (if any) in research settings; and
The approach to analyzing the data.

After the methods section comes a section, variously titled but often called “data,” that takes readers through the analysis. This section is where the thick description narrative; the quotes, broken up by theme or topic, with their interpretation; the discussions of case studies; most data displays (other than perhaps those outlining a theoretical model or summarizing descriptive data about cases); and other similar material appears. The idea of the data section is to give readers the ability to see the data for themselves and to understand how this data supports the ultimate conclusions. Note that all tables and figures included in formal publications should be titled and numbered.

At the end of the paper come one or two summary sections, often called “discussion” and/or “conclusion.” If there is a separate discussion section, it will focus on exploring the overall themes and findings of the paper. The conclusion clearly and succinctly summarizes the findings and conclusions of the paper, the limitations of the research and analysis, any suggestions for future research building on the paper or addressing these limitations, and implications, be they for scholarship and theory or policy and practice.

After the end of the textual material in the paper comes the bibliography, typically called “works cited” or “references.” The references should appear in a consistent citation style—in sociology, we often use the American Sociological Association format (American Sociological Association 2019), but other formats may be used depending on where the piece will eventually be published. Care should be taken to ensure that in-text citations also reflect the chosen citation style. In some papers, there may be an appendix containing supplemental information such as a list of interview questions or an additional data visualization.

Note that when researchers give presentations to scholarly audiences, the presentations typically follow a format similar to that of scholarly papers, though given time limitations they are compressed. Abstracts and works cited are often not part of the presentation, though in-text citations are still used. The literature review presented will be shortened to only focus on the most important aspects of the prior literature, and only key examples from the discussion of data will be included. For long or complex papers, sometimes only one of several findings is the focus of the presentation. Of course, presentations for other audiences may be constructed differently, with greater attention to interesting elements of the data and findings as well as implications and less to the literature review and methods.

Concluding Your Work

After you have written a complete draft of the paper, be sure you take the time to revise and edit your work. There are several important strategies for revision. First, put your work away for a little while. Even waiting a day to revise is better than nothing, but it is best, if possible, to take much more time away from the text. This helps you forget what your writing looks like and makes it easier to find errors, mistakes, and omissions. Second, show your work to others. Ask them to read your work and critique it, pointing out places where the argument is weak, where you may have overlooked alternative explanations, where the writing could be improved, and what else you need to work on. Finally, read your work out loud to yourself (or, if you really need an audience, try reading to some stuffed animals). Reading out loud helps you catch wrong words, tricky sentences, and many other issues. But as important as revision is, try to avoid perfectionism in writing (Warren and Karner 2015). Writing can always be improved, no matter how much time you spend on it. Those improvements, however, have diminishing returns, and at some point the writing process needs to conclude so the writing can be shared with the world.

Of course, the main goal of writing up the results of a research project is to share with others. Thus, researchers should be considering how they intend to disseminate their results. What conferences might be appropriate? Where can the paper be submitted? Note that if you are an undergraduate student, there are a wide variety of journals that accept and publish research conducted by undergraduates. Some publish across disciplines, while others are specific to disciplines. Other work, such as reports, may be best disseminated by publication online on relevant organizational websites.

After a project is completed, be sure to take some time to organize your research materials and archive them for longer-term storage. Some Institutional Review Board (IRB) protocols require that original data, such as interview recordings, transcripts, and field notes, be preserved for a specific number of years in a protected (locked for paper or password-protected for digital) form and then destroyed, so be sure that your plans adhere to the IRB requirements. Be sure you keep any materials that might be relevant for future related research or for answering questions people may ask later about your project.

And then what? Well, then it is time to move on to your next research project. Research is a long-term endeavor, not a one-time-only activity. We build our skills and our expertise as we continue to pursue research. So keep at it.

Find a short article that uses qualitative methods. The sociological magazine Contexts is a good place to find such pieces. Write an abstract of the article.
Choose a sociological journal article on a topic you are interested in that uses some form of qualitative methods and is at least 20 pages long. Rewrite the article as a five-page research summary accessible to non-scholarly audiences.
Choose a concept or idea you have learned in this course and write an explanation of it using the Up-Goer Five Text Editor ( https://www.splasho.com/upgoer5/ ), a website that restricts your writing to the 1,000 most common English words. What was this experience like? What did it teach you about communicating with people who have a more limited English-language vocabulary—and what did it teach you about the utility of having access to complex academic language?
Select five or more sociological journal articles that all use the same basic type of qualitative methods (interviewing, ethnography, documents, or visual sociology). Using what you have learned about coding, code the methods sections of each article, and use your coding to figure out what is common in how such articles discuss their research design, data collection, and analysis methods.
Return to an exercise you completed earlier in this course and revise your work. What did you change? How did revising impact the final product?
Find a quote from the transcript of an interview, a social media post, or elsewhere that has not yet been interpreted or explained. Write a paragraph that includes the quote along with an explanation of its sociological meaning or significance.

The style or personality of a piece of writing, including such elements as tone, word choice, syntax, and rhythm.

A quotation, usually one of some length, which is set off from the main text by being indented on both sides rather than being placed in quotation marks.

A classification of written or artistic work based on form, content, and style.

A short summary of a text written from the perspective of a reader rather than from the perspective of an author.

Social Data Analysis Copyright © 2021 by Mikaila Mariel Lemonik Arthur is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Qualitative and Quantitative Research Methods

Published by Logan Singleton Modified over 8 years ago

Presentation on theme: "Qualitative and Quantitative Research Methods"— Presentation transcript:

Chapter 22 Evaluating a Research Report Gay, Mills, and Airasian

The Robert Gordon University School of Engineering Dr. Mohamed Amish

Research Methods in Crime and Justice

Brief Overview of Qualitative & Quantitative Research.

Modes of Enquiry A Comparison of the Qualitative and Quantitative Approaches.

Methodology A preview. What is Methodology  Choosing a method of data collection  Structure of the research  Builds on and draws from problem statement.

Observing Behavior A nonexperimental approach. QUANTITATIVE AND QUALITATIVE APPROACHES Quantitative Focuses on specific behaviors that can be easily quantified.

Data Analysis, Interpretation, and Reporting

Introduction to Qualitative Research

Chapter 3 Preparing and Evaluating a Research Plan Gay and Airasian

Copyright c 2001 The McGraw-Hill Companies, Inc.1 Chapter 4 Introduction to Qualitative Research Effective in capturing complexity of communication phenomena.

Lecture 2 Research Questions: Defining and Justifying Problems; Defining Hypotheses.

Quantitative and Qualitative Approaches

Outline: Research Methodology: Case Study - what is case study

Quantitative and Qualitative Approaches Dr. William M. Bauer

Qualitative vs. Quantitative QUANTITATIVE Hypothesis: All beans are alike. NULL: No beans are different. Method: Count the beans. QUALITATIVE Question:

QUANTITATIVE & QUALITATIVE RESEARCH IN SOCIAL SCIENCE NGUYEN THU QUYNH – I34035 Introduction to International Relations.

Quantitative (survey) v. Qualitative (field) 1QuantitativeQualitative General framework Seek to test and confirm hypotheses about phenomena. Instruments.

Introduction to Theory & Research Design

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Quantitative and Qualitative research

Jul 28, 2014

770 likes | 1.39k Views

Quantitative and Qualitative research. Quantitative Research. Qualitative Research?. A type of educational research in which the researcher decides what to study. A type of educational research in which the researcher relies on the views of the participants.

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Presentation Transcript

Quantitative Research Qualitative Research? • A type of educational research in which the researcher decides what to study. • A type of educational research in which the researcher relies on the views of the participants.

What are the characteristics of each? Quantitative Research Qualitative Research • Ask broad, general Qs. • Collecting data consisting largely of words (text) or image (picture). • Descriptions and analysis of words for themes. • Conducts inquiry in subjective, biased manner. • Ask specific narrow Qs. • Collects data from participants. • Analyzes numbers using statistics. • Conducts the inquiry in unbiased, objective manner.

What are the differences between the two in each step?

1. Identifying a research problem. Quantitative Research Qualitative Research • Description of trends or an explanation of variables’ relationships. • An exploration in which little is known about the problem. • A detailed understanding of a central phenomenon.

2. Reviewing the literature Quantitative Research Qualitative Research • Major role through suggesting the RQ to be asked. • Justifying the R problem and the need for the direction of the study. • Minor role in suggesting SRQ to be asked. • Justify the importance of studying the research problem.

3. Specifying a purpose for the research Quantitative Research Qualitative Research • Be specific and narrow. • Seek measurable, observable data on variables. • Be general and broad. • Seek to understand the participants’ experiences.

4. Collecting data Quantitative Research Qualitative Research • Collecting data using instruments with preset Qs and Res. • Collecting info from a large number of individuals. • Collecting data using forms with general, emerging Qs to permit the participant to generate responses. • Gathering word(text) or image(picture) data. • Collecting info from a small number of individuals or sites.

5. Analyzing and Interpreting data Quantitative Research Qualitative Research • Data analysis tends to consist of statistical analysis. • Describing trends, comparing group differences, relating variables. • Interpretation tends to consist of comparing results with prior predictions and past research. • Text analysis. • A description of themes. • Stating the larger meaning of findings.

6. Reporting and Evaluating research Quantitative Research Qualitative Research • Tend to use standard fixed structure and evaluation criteria. • Take an objective and unbiased approach. • A flexible, emerging structure and evaluative criteria. • Take a subjective and biased approach.

What are the research designs associated with quantitative and qualitative research?

Research Designs? Research designs are the specific procedures involved in the last three steps of the research process: data collection, data analysis and report writing.

Experimental Designs • An independent variable is manipulated and one or more dependent variables are controlled to see the effect of the independent variable on the dependent variable(s).

Correlational Designs • Looking for relationships between things, even if we don’t have a theory to explain them • “fishing expedition” research - looking for what affects what, trying to find the components for a theory

Survey Designs This involves administration of an instrument to collect data regarding characteristics of a group.

Grounded Disgns • theory that is developed inductively from a corpus of data • Is case-oriented; no hypothesis is tested • Interviews & other data collection can be used • “constant comparison” data set  theory(Source: http://www.scu.edu.au/schools/gcm/ar/arp/grounded.html)

Ethnographic designs • “The study and systematic recording of human cultures; also: a descriptive work produced from such research • Field work; observation, interviews, questionnaires, producing description • Often related to social constructivism: how do people make sense of their world; how do they accomplish things through their practice? • Source: Wikipedia

Narrative Research Designs • In form of stories that describe the lives of individuals and their experiences.

Mixed Method Studies • Some studies use mixed methods to collect and analyze data…both quantitative and qualitative. For example, a person might do a quantitative survey and follow it up with qualitative interviews or focus groups. Again, the question dictates the method.

Action Designs • disciplined inquiry into practices undertaken by those involved in them • done to inform and change the practice studied. To address problems • Often undertaken as a collaborative activity among colleagues • Often undertaken in situ • Could focus on a single issue in a classroom, a program, etc.

Action Designs • a cycle of posing questions, gathering data, reflection, and deciding on a course of action • Source: http://www.alliance.brown.edu/pubs/themes_ed/act_research.pdf • Source: http://en.wikipedia.org/wiki/Participatory_action_research

How do you choose which type of research to use?

Match your approach to your research problem • Fit the approach to your audience. • Relate the approach to your experience.

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QUALITATIVE AND QUANTITATIVE RESEARCH

In this lecture, delivered at Seacom Skills University, I have discussed qualitative and quantitative research.The lecture will be useful to students of social sciences.

Related Papers

Tshidi M Wyllie

To accumulate a body of knowledge which can inform and improve socio-economic and political human existence requires evidence-based approaches, as such, conducting scientific researches is usually carried out to find solutions to a prevailing phenomenon; therefore, extracting and accumulating such a scientific knowledge and/or information is a crucial process. In this endeavour, researchers usually deploy various scientific approaches and methods; methods which are mostly informed by ontological and epistemological underpinnings. In discussing quantitative and qualitative research approaches and drawing distinction between the two approaches this paper will explain the three major dimensions considered critical in research process

iosrjournals.org

Munyaradzi Moyo

International Journal of Scientific Research and Management (IJSRM)

Ernest Negou

The objective of this study is to provide a guide to qualitative research methodology in social sciences. It is the result of the observation that research in Management Sciences in most Universities in Cameroon is still dominated by the quantitative approach supported by economists who handle most research methodology courses. In an environment of oral tradition and the difficulties to have access to data, emphasising purely quantitative research may leave aside many aspects of the environment and several areas of human behaviour that make its specificities. Therefore, there is a need to generalise the use of qualitative research to enable researchers to always have a good insight into phenomena not yet clarified before thinking of any generalisation which is the main objective of quantitative research: this gives room to the contextualisation of research which results can easily be applied in its context, thus, enhancing development.

Kirathe Wanjiku

Tracie Seidelman

Forum Qualitative Sozialforschung Forum Qualitative Social Research

Margrit Schreier

M.Lib.I.Sc. Project, Panjab University, under guidance of Dr. Shiv Kumar

SUBHAJIT PANDA

There's no hard and fast rule for qualitative versus quantitative research, and it's often taken for granted. It is claimed here that the divide between qualitative and quantitative research is ambiguous, incoherent, and hence of little value, and that its widespread use could have negative implications. This conclusion is supported by a variety of arguments. Qualitative researchers, for example, have varying perspectives on fundamental problems (such as the use of quantification and causal analysis), which makes the difference as such shaky. In addition, many elements of qualitative and quantitative research overlap significantly, making it difficult to distinguish between the two. Practically in the case of field research, the Qualitative and quantitative approach can't be distinguished clearly as the study pointed. The distinction may limit innovation in the development of new research methodologies, as well as cause complication and wasteful activity. As a general rule, it may be desirable not to conceptualise research approaches at such abstract levels as are done in the context of qualitative or quantitative methodologies. Discussions of the benefits and drawbacks of various research methods, rather than general research questions, are recommended.

IRJET Journal

Research design methods, such as qualitative, quantitative as well as mixed methods were introduced and subsequently each method was discussed in detail with the help of literature review as well as some personal and live examples to substantiate the findings of various literature. From various literature as well as from the own experiences, it is concluded that both qualitative research design method and quantitative research design method are equally important. It is not fair to criticize one method as the researcher is inclined towards the other method. It is practically evidenced that usage of both methods in the research, the researcher can substantiate the case better. However, duration part while using mixed methods to be kept in mind as it will take more time compared to the qualitative and quantitative methods. Hurrying and aborting in the middle due to time constraint ultimately result in poor research. It would be better if the world view towards these methods changes from criticizing mode to effective utilization mode, which will help research community in focusing and bring up better research outcomes rather than wasting time in arguing which method is scientifically acceptable and which method is biased. While I agree that the ontological, epistemological, axiological, and methodological assumptions for qualitative research method and quantitative research method, researchers should know fully about these methods and keep them as effective tools to utilize them in mixed mode, wherever it is appropriate and required to arrive at adequate research findings.

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Qualitative vs. Quantitative Research | Differences, Examples & Methods

Table of contents

Quantitative data collection methods

Qualitative data collection methods

Quantitative research approach

Qualitative research approach

Mixed methods approach

Analyzing quantitative data

Analyzing qualitative data

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Qualitative vs Quantitative Research Methods & Data Analysis

What is the difference between quantitative and qualitative?

What Is Qualitative Research?

Qualitative Methods

Qualitative Data Analysis

Key Features

Limitations of Qualitative Research

Advantages of Qualitative Research

What Is Quantitative Research?

Quantitative Methods

Quantitative Data Analysis

Limitations of Quantitative Research

Advantages of Quantitative Research

Further Information

Chapter 20. Presentations

Writing about Your Research

Make an Argument

Presenting at Conferences and Job Talks

A Word on Universal Design

Poster Design

Incorporating Visual Design in Your Presentations

Ethics of Presentation and Reliability

Final Comments: Preparing for Being Challenged

Data Visualization Checklist for Slideshow (PPT) Presentations

Universal Design Checklist for Slideshow (PPT) Presentations

Supplement: Models of Written Sections for Future Reference

Justification of Case Selection / Sample Description Section Example

Ethics Section Example

Further Readings

Quantitative vs. Qualitative Research in Psychology

Quantitative Research Methods

At a Glance

Qualitative Research vs. Quantitative Research

Basic Assumptions

Correlation and Causation

Pitfalls of Quantitative Research

Qualitative Approaches

Interpretation

Relationship Between Qualitative and Quantitative Research

Presenting and Evaluating Qualitative Research

INTRODUCTION

RIGOUR IN QUALITATIVE RESEARCH

STRENGTHS AND LIMITATIONS OF QUALITATIVE RESEARCH

Strengths of Qualitative Research

Limitations of Qualitative Research

PRESENTATION OF QUALITATIVE RESEARCH FINDINGS

Data From an Interview.

Data From Observations

Data From Focus Groups

GUIDANCE FOR PUBLISHING QUALITATIVE RESEARCH

Introduction.

Data Analysis.

Discussion.

Conclusion.

CHECKLIST FOR QUALITATIVE PAPERS

ACKNOWLEDGEMENTS

Appendix 1. Checklist for authors and reviewers of qualitative research.

Feedback in the Writing Process

Obtaining Feedback with Qualitative Research

Obtaining Feedback with Quantitative Research

What Is Validity?

What Is Reliability?

What Is Statistically Significant?

KEY TAKEAWAY

[Guide] How to Present Qualitative Research Findings in PowerPoint?

How to Create a Structure for your Qualitative Research Presentation?

1. Objective of the Research