examples of qualitative vs quantitative research

Educational resources and simple solutions for your research journey

Qualitative vs Quantitative Research: Differences, Examples, and Methods

There are two broad kinds of research approaches: qualitative and quantitative research that are used to study and analyze phenomena in various fields such as natural sciences, social sciences, and humanities. Whether you have realized it or not, your research must have followed either or both research types. In this article we will discuss what qualitative vs quantitative research is, their applications, pros and cons, and when to use qualitative vs quantitative research . Before we get into the details, it is important to understand the differences between the qualitative and quantitative research.     

Table of Contents

Qualitative v s Quantitative Research  

Quantitative research deals with quantity, hence, this research type is concerned with numbers and statistics to prove or disapprove theories or hypothesis. In contrast, qualitative research is all about quality – characteristics, unquantifiable features, and meanings to seek deeper understanding of behavior and phenomenon. These two methodologies serve complementary roles in the research process, each offering unique insights and methods suited to different research questions and objectives.    

Qualitative and quantitative research approaches have their own unique characteristics, drawbacks, advantages, and uses. Where quantitative research is mostly employed to validate theories or assumptions with the goal of generalizing facts to the larger population, qualitative research is used to study concepts, thoughts, or experiences for the purpose of gaining the underlying reasons, motivations, and meanings behind human behavior .   

What Are the Differences Between Qualitative and Quantitative Research  

Qualitative and quantitative research differs in terms of the methods they employ to conduct, collect, and analyze data. For example, qualitative research usually relies on interviews, observations, and textual analysis to explore subjective experiences and diverse perspectives. While quantitative data collection methods include surveys, experiments, and statistical analysis to gather and analyze numerical data. The differences between the two research approaches across various aspects are listed in the table below.    

Data Collection Methods  

There are differences between qualitative and quantitative research when it comes to data collection as they deal with different types of data. Qualitative research is concerned with personal or descriptive accounts to understand human behavior within society. Quantitative research deals with numerical or measurable data to delineate relations among variables. Hence, the qualitative data collection methods differ significantly from quantitative data collection methods due to the nature of data being collected and the research objectives. Below is the list of data collection methods for each research approach:    

Qualitative Research Data Collection  

• Interviews  
• Focus g roups  
• Content a nalysis  
• Literature review  
• Observation  
• Ethnography  

Qualitative research data collection can involve one-on-one group interviews to capture in-depth perspectives of participants using open-ended questions. These interviews could be structured, semi-structured or unstructured depending upon the nature of the study. Focus groups can be used to explore specific topics and generate rich data through discussions among participants. Another qualitative data collection method is content analysis, which involves systematically analyzing text documents, audio, and video files or visual content to uncover patterns, themes, and meanings. This can be done through coding and categorization of raw data to draw meaningful insights. Data can be collected through observation studies where the goal is to simply observe and document behaviors, interaction, and phenomena in natural settings without interference. Lastly, ethnography allows one to immerse themselves in the culture or environment under study for a prolonged period to gain a deep understanding of the social phenomena.   

Quantitative Research Data Collection  

• Surveys/ q uestionnaires  
• Experiments
• Secondary data analysis  
• Structured o bservations  
• Case studies   
• Tests and a ssessments  

Quantitative research data collection approaches comprise of fundamental methods for generating numerical data that can be analyzed using statistical or mathematical tools. The most common quantitative data collection approach is the usage of structured surveys with close-ended questions to collect quantifiable data from a large sample of participants. These can be conducted online, over the phone, or in person.   

Performing experiments is another important data collection approach, in which variables are manipulated under controlled conditions to observe their effects on dependent variables. This often involves random assignment of participants to different conditions or groups. Such experimental settings are employed to gauge cause-and-effect relationships and understand a complex phenomenon. At times, instead of acquiring original data, researchers may deal with secondary data, which is the dataset curated by others, such as government agencies, research organizations, or academic institute. With structured observations, subjects in a natural environment can be studied by controlling the variables which aids in understanding the relationship among various variables. The secondary data is then analyzed to identify patterns and relationships among variables. Observational studies provide a means to systematically observe and record behaviors or phenomena as they occur in controlled environments. Case studies form an interesting study methodology in which a researcher studies a single entity or a small number of entities (individuals or organizations) in detail to understand complex phenomena within a specific context.   

Qualitative vs Quantitative Research Outcomes  

Qualitative research and quantitative research lead to varied research outcomes, each with its own strengths and limitations. For example, qualitative research outcomes provide deep descriptive accounts of human experiences, motivations, and perspectives that allow us to identify themes or narratives and context in which behavior, attitudes, or phenomena occurs.  Quantitative research outcomes on the other hand produce numerical data that is analyzed statistically to establish patterns and relationships objectively, to form generalizations about the larger population and make predictions. This numerical data can be presented in the form of graphs, tables, or charts. Both approaches offer valuable perspectives on complex phenomena, with qualitative research focusing on depth and interpretation, while quantitative research emphasizes numerical analysis and objectivity.  

When to Use Qualitative vs Quantitative Research Approach  

The decision to choose between qualitative and quantitative research depends on various factors, such as the research question, objectives, whether you are taking an inductive or deductive approach, available resources, practical considerations such as time and money, and the nature of the phenomenon under investigation. To simplify, quantitative research can be used if the aim of the research is to prove or test a hypothesis, while qualitative research should be used if the research question is more exploratory and an in-depth understanding of the concepts, behavior, or experiences is needed.     

Qualitative research approach  

Qualitative research approach is used under following scenarios:   

• To study complex phenomena: When the research requires understanding the depth, complexity, and context of a phenomenon.  
• Collecting participant perspectives: When the goal is to understand the why behind a certain behavior, and a need to capture subjective experiences and perceptions of participants.  
• Generating hypotheses or theories: When generating hypotheses, theories, or conceptual frameworks based on exploratory research.  

Example: If you have a research question “What obstacles do expatriate students encounter when acquiring a new language in their host country?”  

This research question can be addressed using the qualitative research approach by conducting in-depth interviews with 15-25 expatriate university students. Ask open-ended questions such as “What are the major challenges you face while attempting to learn the new language?”, “Do you find it difficult to learn the language as an adult?”, and “Do you feel practicing with a native friend or colleague helps the learning process”?  

Based on the findings of these answers, a follow-up questionnaire can be planned to clarify things. Next step will be to transcribe all interviews using transcription software and identify themes and patterns.   

Quantitative research approach  

Quantitative research approach is used under following scenarios:   

• Testing hypotheses or proving theories: When aiming to test hypotheses, establish relationships, or examine cause-and-effect relationships.   
• Generalizability: When needing findings that can be generalized to broader populations using large, representative samples.  
• Statistical analysis: When requiring rigorous statistical analysis to quantify relationships, patterns, or trends in data.   

Example : Considering the above example, you can conduct a survey of 200-300 expatriate university students and ask them specific questions such as: “On a scale of 1-10 how difficult is it to learn a new language?”  

Next, statistical analysis can be performed on the responses to draw conclusions like, on an average expatriate students rated the difficulty of learning a language 6.5 on the scale of 10.    

Mixed methods approach  

In many cases, researchers may opt for a mixed methods approach , combining qualitative and quantitative methods to leverage the strengths of both approaches. Researchers may use qualitative data to explore phenomena in-depth and generate hypotheses, while quantitative data can be used to test these hypotheses and generalize findings to broader populations.  

Example: Both qualitative and quantitative research methods can be used in combination to address the above research question. Through open-ended questions you can gain insights about different perspectives and experiences while quantitative research allows you to test that knowledge and prove/disprove your hypothesis.   

How to Analyze Qualitative and Quantitative Data  

When it comes to analyzing qualitative and quantitative data, the focus is on identifying patterns in the data to highlight the relationship between elements. The best research method for any given study should be chosen based on the study aim. A few methods to analyze qualitative and quantitative data are listed below.  

Analyzing qualitative data  

Qualitative data analysis is challenging as it is not expressed in numbers and consists majorly of texts, images, or videos. Hence, care must be taken while using any analytical approach. Some common approaches to analyze qualitative data include:  

• Organization: The first step is data (transcripts or notes) organization into different categories with similar concepts, themes, and patterns to find inter-relationships.  
• Coding: Data can be arranged in categories based on themes/concepts using coding.  
• Theme development: Utilize higher-level organization to group related codes into broader themes.  
• Interpretation: Explore the meaning behind different emerging themes to understand connections. Use different perspectives like culture, environment, and status to evaluate emerging themes.  
• Reporting: Present findings with quotes or excerpts to illustrate key themes.   

Analyzing quantitative data  

Quantitative data analysis is more direct compared to qualitative data as it primarily deals with numbers. Data can be evaluated using simple math or advanced statistics (descriptive or inferential). Some common approaches to analyze quantitative data include:  

• Processing raw data: Check missing values, outliers, or inconsistencies in raw data.  
• Descriptive statistics: Summarize data with means, standard deviations, or standard error using programs such as Excel, SPSS, or R language.  
• Exploratory data analysis: Usage of visuals to deduce patterns and trends.  
• Hypothesis testing: Apply statistical tests to find significance and test hypothesis (Student’s t-test or ANOVA).  
• Interpretation: Analyze results considering significance and practical implications.  
• Validation: Data validation through replication or literature review.  
• Reporting: Present findings by means of tables, figures, or graphs.   

Benefits and limitations of qualitative vs quantitative research  

There are significant differences between qualitative and quantitative research; we have listed the benefits and limitations of both methods below:  

Benefits of qualitative research  

• Rich insights: As qualitative research often produces information-rich data, it aids in gaining in-depth insights into complex phenomena, allowing researchers to explore nuances and meanings of the topic of study.  
• Flexibility: One of the most important benefits of qualitative research is flexibility in acquiring and analyzing data that allows researchers to adapt to the context and explore more unconventional aspects.  
• Contextual understanding: With descriptive and comprehensive data, understanding the context in which behaviors or phenomena occur becomes accessible.   
• Capturing different perspectives: Qualitative research allows for capturing different participant perspectives with open-ended question formats that further enrich data.   
• Hypothesis/theory generation: Qualitative research is often the first step in generating theory/hypothesis, which leads to future investigation thereby contributing to the field of research.

Limitations of qualitative research  

• Subjectivity: It is difficult to have objective interpretation with qualitative research, as research findings might be influenced by the expertise of researchers. The risk of researcher bias or interpretations affects the reliability and validity of the results.   
• Limited generalizability: Due to the presence of small, non-representative samples, the qualitative data cannot be used to make generalizations to a broader population.  
• Cost and time intensive: Qualitative data collection can be time-consuming and resource-intensive, therefore, it requires strategic planning and commitment.   
• Complex analysis: Analyzing qualitative data needs specialized skills and techniques, hence, it’s challenging for researchers without sufficient training or experience.   
• Potential misinterpretation: There is a risk of sampling bias and misinterpretation in data collection and analysis if researchers lack cultural or contextual understanding.   

Benefits of quantitative research  

• Objectivity: A key benefit of quantitative research approach, this objectivity reduces researcher bias and subjectivity, enhancing the reliability and validity of findings.   
• Generalizability: For quantitative research, the sample size must be large and representative enough to allow for generalization to broader populations.   
• Statistical analysis: Quantitative research enables rigorous statistical analysis (increasing power of the analysis), aiding hypothesis testing and finding patterns or relationship among variables.   
• Efficiency: Quantitative data collection and analysis is usually more efficient compared to the qualitative methods, especially when dealing with large datasets.   
• Clarity and Precision: The findings are usually clear and precise, making it easier to present them as graphs, tables, and figures to convey them to a larger audience.  

Limitations of quantitative research  

• Lacks depth and details: Due to its objective nature, quantitative research might lack the depth and richness of qualitative approaches, potentially overlooking important contextual factors or nuances.   
• Limited exploration: By not considering the subjective experiences of participants in depth , there’s a limited chance to study complex phenomenon in detail.   
• Potential oversimplification: Quantitative research may oversimplify complex phenomena by boiling them down to numbers, which might ignore key nuances.   
• Inflexibility: Quantitative research deals with predecided varibales and measures , which limits the ability of researchers to explore unexpected findings or adjust the research design as new findings become available .  
• Ethical consideration: Quantitative research may raise ethical concerns especially regarding privacy, informed consent, and the potential for harm, when dealing with sensitive topics or vulnerable populations.   

Frequently asked questions  

• What is the difference between qualitative and quantitative research? 

Quantitative methods use numerical data and statistical analysis for objective measurement and hypothesis testing, emphasizing generalizability. Qualitative methods gather non-numerical data to explore subjective experiences and contexts, providing rich, nuanced insights.  

• What are the types of qualitative research? 

Qualitative research methods include interviews, observations, focus groups, and case studies. They provide rich insights into participants’ perspectives and behaviors within their contexts, enabling exploration of complex phenomena.  

• What are the types of quantitative research? 

Quantitative research methods include surveys, experiments, observations, correlational studies, and longitudinal research. They gather numerical data for statistical analysis, aiming for objectivity and generalizability.  

• Can you give me examples for qualitative and quantitative research? 

Qualitative Research Example: 

Research Question: What are the experiences of parents with autistic children in accessing support services?  

Method: Conducting in-depth interviews with parents to explore their perspectives, challenges, and needs.  

Quantitative Research Example: 

Research Question: What is the correlation between sleep duration and academic performance in college students?  

Method: Distributing surveys to a large sample of college students to collect data on their sleep habits and academic performance, then analyzing the data statistically to determine any correlations.  

Researcher.Life is a subscription-based platform that unifies the best AI tools and services designed to speed up, simplify, and streamline every step of a researcher’s journey. The Researcher.Life All Access Pack is a one-of-a-kind subscription that unlocks full access to an AI writing assistant, literature recommender, journal finder, scientific illustration tool, and exclusive discounts on professional publication services from Editage.  

Based on 21+ years of experience in academia, Researcher.Life All Access empowers researchers to put their best research forward and move closer to success. Explore our top AI Tools pack, AI Tools + Publication Services pack, or Build Your Own Plan. Find everything a researcher needs to succeed, all in one place –  Get All Access now starting at just $17 a month !    

Related Posts

Essay Writing Basics: Strategies for PhD Success 

Streamlining the Research Funding Journey With Researcher.Life’s GrantDesk

Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

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

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Qualitative vs Quantitative Research | Examples & Methods

Qualitative vs Quantitative Research | Examples & Methods

Published on 4 April 2022 by Raimo Streefkerk . Revised on 8 May 2023.

When collecting and analysing 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. 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.

Table of contents

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

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

Prevent plagiarism, run a free check.

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, observations 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 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 organisation 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 analysed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analysing quantitative data

Quantitative data is based on numbers. Simple maths 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
• 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

Analysing qualitative data

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

Some common approaches to analysing 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

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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 analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are 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 organisations.

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

• Prepare and organise 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 .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Streefkerk, R. (2023, May 08). Qualitative vs Quantitative Research | Examples & Methods. Scribbr. Retrieved 1 April 2024, from https://www.scribbr.co.uk/research-methods/quantitative-qualitative-research/

Is this article helpful?

Raimo Streefkerk

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

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.

• 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.

Brady HE. Causation and explanation in social science . In: Goodin RE, ed. The Oxford Handbook of Political Science. Oxford University Press; 2011. doi:10.1093/oxfordhb/9780199604456.013.0049

Chun Tie Y, Birks M, Francis K. Grounded theory research: A design framework for novice researchers .  SAGE Open Med . 2019;7:2050312118822927. doi:10.1177/2050312118822927

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

Salkind NJ, ed. Encyclopedia of Research Design . Sage Publishing.

Shaughnessy JJ, Zechmeister EB, Zechmeister JS.  Research Methods in Psychology . McGraw Hill Education.

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.

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Qualitative vs Quantitative Research: Differences and Examples

Understanding the differences between qualitative vs quantitative research is essential when conducting a research project, as both methods underpin the two key approaches in conducting a study.

In recent blogs, we elaborately discussed quantitative and qualitative research methods b ut what is the difference between the two? Which one is the best? Let’s find out.

Qualitative Research In a nutshell

Qualitative research is a research methodology where “quality” or opinion based research is conducted to derive research conclusions. This type of research is often conversational in nature rather than being quantifiable through empirical research and measurements.

Qualitative research: Methods & Characteristics

1. Conversation : A conversation takes place between the researcher and the respondent. This can be in the form of focus groups , in-depth interviews using telephonic / video / face-to-face conversations.

However, with the rise of online platforms, a bulk of steps in qualitative research involves creating and maintaining online community portals for a more quantifiable and recordable qualitative study.

LEARN ABOUT: Qualitative Interview

2. Conclusions : Research conclusions are subjective in nature when conducting qualitative research. The researcher may derive conclusions based on in-depth analysis of respondent attitude, reason behind responses and understanding of psychological motivations.

Quantitative Research In a nutshell

Quantitative research is a research methodology which uses questions and questionnaires to gather quantifiable data and perform statistical analysis to derive meaningful research conclusions.

Quantitative research: Methods & Characteristics

1. Questions : Quantitative research method uses surveys and polls to gather information on a given subject. There are a variety of question types used based on a nature of the research study.

For Example: If you want to conduct a customer satisfaction quantitative research, the Net Promoter Score is one of the critically acclaimed survey questions for this purpose.

2. Distribution : Quantitative research uses email surveys as the primary mode of gathering responses to questions. Alternatively, technology has given rise to offline distribution methods for relatively remote locations using offline mobile data capture apps. For social sciences and psychological quantitative research, social media surveys are also used to gather data.

3. Statistical Analysis : Quantitative research uses a wide range of data analysis techniques such as Conjoint Analysis , Cross Tabulation and Trend Analysis .

Qualitative vs Quantitative Research

Now let’s compare the qualitative and quantitative research methods in different aspects so that you can choose the right one in your next investigation.:

1. Objective and flow of research

Quantitative research is used in data-oriented research where the objective of research design is to derive “measurable empirical evidence” based on fixed and pre-determined questions. The flow of research, is therefore, decided before the research is conducted.

Where as, qualitative research is used where the objective is research is to keep probing the respondents based on previous answers under the complete discretion of the interviewer. The flow of research is not determined and the researcher / interviewer has the liberty to frame and ask new questions.

2. Respondent sample size

Respondents or sample of a particular panel is much larger for quantitative research such that enough verifiable information is gather to reach a conclusion without opinion bias. In large scale quantitative research, sample size can be in thousands.

Where as, qualitative research inherently uses less sample size because a large sample size makes it difficult of the research to probe respondents. For instance, a typical political focus group study evaluating election candidates involves no more than 5-10 panelists.

3. Information gathering

Quantitative research uses information gathering methods that can be quantified and processed for statistical analysis techniques. Simply put – quantitative research is heavily dependent on “numbers”, data and stats.

LEARN ABOUT: Research Process Steps

Where as, qualitative research uses conversational methods to gather relevant information on a given subject.

4. Post-research response analysis and conclusions

Quantitative research uses a variety of statistical analysis methods to derive quantifiable research conclusions. These are based on mathematical processes applied on the gather data.

Where as, qualitative researc h depends on the interviewer to derive research conclusions based on qualitative conversations held with the respondents. This conclusion is effectively subjective in nature. This is why quantitative research recordings are often reviewed by senior researchers before the final research conclusion is drawn.

Differences between qualitative vs quantitative research

We hope that this information helps you choose your next research method and achieve your goals.

If you want to carry out any qualitative or qualitative research questions , ask about the tools that QuestionPro has available to help you with the qualitative data collection of the data you need. We have functions for all types of research!.

MORE LIKE THIS

Customer Experience Automation: Benefits and Best Tools

Apr 1, 2024

7 Best Market Segmentation Tools in 2024

In-App Feedback Tools: How to Collect, Uses & 14 Best Tools

Mar 29, 2024

11 Best Customer Journey Analytics Software in 2024

Other categories.

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

Qualitative vs. Quantitative Research: Comparing the Methods and Strategies for Education Research

No matter the field of study, all research can be divided into two distinct methodologies: qualitative and quantitative research. Both methodologies offer education researchers important insights.

Education research assesses problems in policy, practices, and curriculum design, and it helps administrators identify solutions. Researchers can conduct small-scale studies to learn more about topics related to instruction or larger-scale ones to gain insight into school systems and investigate how to improve student outcomes.

Education research often relies on the quantitative methodology. Quantitative research in education provides numerical data that can prove or disprove a theory, and administrators can easily share the number-based results with other schools and districts. And while the research may speak to a relatively small sample size, educators and researchers can scale the results from quantifiable data to predict outcomes in larger student populations and groups.

Qualitative vs. Quantitative Research in Education: Definitions

Although there are many overlaps in the objectives of qualitative and quantitative research in education, researchers must understand the fundamental functions of each methodology in order to design and carry out an impactful research study. In addition, they must understand the differences that set qualitative and quantitative research apart in order to determine which methodology is better suited to specific education research topics.

Generate Hypotheses with Qualitative Research

Qualitative research focuses on thoughts, concepts, or experiences. The data collected often comes in narrative form and concentrates on unearthing insights that can lead to testable hypotheses. Educators use qualitative research in a study’s exploratory stages to uncover patterns or new angles.

Form Strong Conclusions with Quantitative Research

Quantitative research in education and other fields of inquiry is expressed in numbers and measurements. This type of research aims to find data to confirm or test a hypothesis.

Differences in Data Collection Methods

Keeping in mind the main distinction in qualitative vs. quantitative research—gathering descriptive information as opposed to numerical data—it stands to reason that there are different ways to acquire data for each research methodology. While certain approaches do overlap, the way researchers apply these collection techniques depends on their goal.

Interviews, for example, are common in both modes of research. An interview with students that features open-ended questions intended to reveal ideas and beliefs around attendance will provide qualitative data. This data may reveal a problem among students, such as a lack of access to transportation, that schools can help address.

An interview can also include questions posed to receive numerical answers. A case in point: how many days a week do students have trouble getting to school, and of those days, how often is a transportation-related issue the cause? In this example, qualitative and quantitative methodologies can lead to similar conclusions, but the research will differ in intent, design, and form.

Taking a look at behavioral observation, another common method used for both qualitative and quantitative research, qualitative data may consider a variety of factors, such as facial expressions, verbal responses, and body language.

On the other hand, a quantitative approach will create a coding scheme for certain predetermined behaviors and observe these in a quantifiable manner.

Qualitative Research Methods

• Case Studies : Researchers conduct in-depth investigations into an individual, group, event, or community, typically gathering data through observation and interviews.
• Focus Groups : A moderator (or researcher) guides conversation around a specific topic among a group of participants.
• Ethnography : Researchers interact with and observe a specific societal or ethnic group in their real-life environment.
• Interviews : Researchers ask participants questions to learn about their perspectives on a particular subject.

Quantitative Research Methods

• Questionnaires and Surveys : Participants receive a list of questions, either closed-ended or multiple choice, which are directed around a particular topic.
• Experiments : Researchers control and test variables to demonstrate cause-and-effect relationships.
• Observations : Researchers look at quantifiable patterns and behavior.
• Structured Interviews : Using a predetermined structure, researchers ask participants a fixed set of questions to acquire numerical data.

Choosing a Research Strategy

When choosing which research strategy to employ for a project or study, a number of considerations apply. One key piece of information to help determine whether to use a qualitative vs. quantitative research method is which phase of development the study is in.

For example, if a project is in its early stages and requires more research to find a testable hypothesis, qualitative research methods might prove most helpful. On the other hand, if the research team has already established a hypothesis or theory, quantitative research methods will provide data that can validate the theory or refine it for further testing.

It’s also important to understand a project’s research goals. For instance, do researchers aim to produce findings that reveal how to best encourage student engagement in math? Or is the goal to determine how many students are passing geometry? These two scenarios require distinct sets of data, which will determine the best methodology to employ.

In some situations, studies will benefit from a mixed-methods approach. Using the goals in the above example, one set of data could find the percentage of students passing geometry, which would be quantitative. The research team could also lead a focus group with the students achieving success to discuss which techniques and teaching practices they find most helpful, which would produce qualitative data.

Learn How to Put Education Research into Action

Those with an interest in learning how to harness research to develop innovative ideas to improve education systems may want to consider pursuing a doctoral degree. American University’s School of Education Online offers a Doctor of Education (EdD) in Education Policy and Leadership that prepares future educators, school administrators, and other education professionals to become leaders who effect positive changes in schools. Courses such as Applied Research Methods I: Enacting Critical Research provides students with the techniques and research skills needed to begin conducting research exploring new ways to enhance education. Learn more about American’ University’s EdD in Education Policy and Leadership .

What’s the Difference Between Educational Equity and Equality?

EdD vs. PhD in Education: Requirements, Career Outlook, and Salary

Top Education Technology Jobs for Doctorate in Education Graduates

American University, EdD in Education Policy and Leadership

Edutopia, “2019 Education Research Highlights”

Formplus, “Qualitative vs. Quantitative Data: 15 Key Differences and Similarities”

iMotion, “Qualitative vs. Quantitative Research: What Is What?”

Scribbr, “Qualitative vs. Quantitative Research”

Simply Psychology, “What’s the Difference Between Quantitative and Qualitative Research?”

Typeform, “A Simple Guide to Qualitative and Quantitative Research”

Request Information

Qualitative vs Quantitative Research 101

A plain-language explanation (with examples).

By: Kerryn Warren (PhD, MSc, BSc) | June 2020

So, it’s time to decide what type of research approach you’re going to use – qualitative or quantitative . And, chances are, you want to choose the one that fills you with the least amount of dread. The engineers may be keen on quantitative methods because they loathe interacting with human beings and dealing with the “soft” stuff and are far more comfortable with numbers and algorithms. On the other side, the anthropologists are probably more keen on qualitative methods because they literally have the opposite fears.

However, when justifying your research, “being afraid” is not a good basis for decision making. Your methodology needs to be informed by your research aims and objectives , not your comfort zone. Plus, it’s quite common that the approach you feared (whether qualitative or quantitative) is actually not that big a deal. Research methods can be learnt (usually a lot faster than you think) and software reduces a lot of the complexity of both quantitative and qualitative data analysis. Conversely, choosing the wrong approach and trying to fit a square peg into a round hole is going to create a lot more pain.

In this post, I’ll explain the qualitative vs quantitative choice in straightforward, plain language with loads of examples. This won’t make you an expert in either, but it should give you a good enough “big picture” understanding so that you can make the right methodological decision for your research.

Qualitative vs Quantitative: Overview  

• Qualitative analysis 101
• Quantitative analysis 101
• How to choose which one to use
• Data collection and analysis for qualitative and quantitative research
• The pros and cons of both qualitative and quantitative research
• A quick word on mixed methods

Qualitative Research 101: The Basics

The bathwater is hot.

Let us unpack that a bit. What does that sentence mean? And is it useful?

The answer is: well, it depends. If you’re wanting to know the exact temperature of the bath, then you’re out of luck. But, if you’re wanting to know how someone perceives the temperature of the bathwater, then that sentence can tell you quite a bit if you wear your qualitative hat .

Many a husband and wife have never enjoyed a bath together because of their strongly held, relationship-destroying perceptions of water temperature (or, so I’m told). And while divorce rates due to differences in water-temperature perception would belong more comfortably in “quantitative research”, analyses of the inevitable arguments and disagreements around water temperature belong snugly in the domain of “qualitative research”. This is because qualitative research helps you understand people’s perceptions and experiences  by systematically coding and analysing the data .

With qualitative research, those heated disagreements (excuse the pun) may be analysed in several ways. From interviews to focus groups to direct observation (ideally outside the bathroom, of course). You, as the researcher, could be interested in how the disagreement unfolds, or the emotive language used in the exchange. You might not even be interested in the words at all, but in the body language of someone who has been forced one too many times into (what they believe) was scalding hot water during what should have been a romantic evening. All of these “softer” aspects can be better understood with qualitative research.

In this way, qualitative research can be incredibly rich and detailed , and is often used as a basis to formulate theories and identify patterns. In other words, it’s great for exploratory research (for example, where your objective is to explore what people think or feel), as opposed to confirmatory research (for example, where your objective is to test a hypothesis). Qualitative research is used to understand human perception , world view and the way we describe our experiences. It’s about exploring and understanding a broad question, often with very few preconceived ideas as to what we may find.

But that’s not the only way to analyse bathwater, of course…

Quantitative Research 101: The Basics

The bathwater is 45 degrees Celsius.

Now, what does this mean? How can this be used?

I was once told by someone to whom I am definitely not married that he takes regular cold showers. As a person who is terrified of anything that isn’t body temperature or above, this seemed outright ludicrous. But this raises a question: what is the perfect temperature for a bath? Or at least, what is the temperature of people’s baths more broadly? (Assuming, of course, that they are bathing in water that is ideal to them). To answer this question, you need to now put on your quantitative hat .

If we were to ask 100 people to measure the temperature of their bathwater over the course of a week, we could get the average temperature for each person. Say, for instance, that Jane averages at around 46.3°C. And Billy averages around 42°C. A couple of people may like the unnatural chill of 30°C on the average weekday. And there will be a few of those striving for the 48°C that is apparently the legal limit in England (now, there’s a useless fact for you).

With a quantitative approach, this data can be analysed in heaps of ways. We could, for example, analyse these numbers to find the average temperature, or look to see how much these temperatures vary. We could see if there are significant differences in ideal water temperature between the sexes, or if there is some relationship between ideal bath water temperature and age! We could pop this information onto colourful, vibrant graphs , and use fancy words like “significant”, “correlation” and “eigenvalues”. The opportunities for nerding out are endless…

In this way, quantitative research often involves coming into your research with some level of understanding or expectation regarding the outcome, usually in the form of a hypothesis that you want to test. For example:

Hypothesis: Men prefer bathing in lower temperature water than women do.

This hypothesis can then be tested using statistical analysis. The data may suggest that the hypothesis is sound, or it may reveal that there are some nuances regarding people’s preferences. For example, men may enjoy a hotter bath on certain days.

So, as you can see, qualitative and quantitative research each have their own purpose and function. They are, quite simply, different tools for different jobs .

Need a helping hand?

Qualitative vs Quantitative Research: Which one should you use?

And here I become annoyingly vague again. The answer: it depends. As I alluded to earlier, your choice of research approach depends on what you’re trying to achieve with your research. 

If you want to understand a situation with richness and depth , and you don’t have firm expectations regarding what you might find, you’ll likely adopt a qualitative research approach. In other words, if you’re starting on a clean slate and trying to build up a theory (which might later be tested), qualitative research probably makes sense for you.

On the other hand, if you need to test an already-theorised hypothesis , or want to measure and describe something numerically, a quantitative approach will probably be best. For example, you may want to quantitatively test a theory (or even just a hypothesis) that was developed using qualitative research.

Basically, this means that your research approach should be chosen based on your broader research aims , objectives and research questions . If your research is exploratory and you’re unsure what findings may emerge, qualitative research allows you to have open-ended questions and lets people and subjects speak, in some ways, for themselves. Quantitative questions, on the other hand, will not. They’ll often be pre-categorised, or allow you to insert a numeric response. Anything that requires measurement , using a scale, machine or… a thermometer… is going to need a quantitative method.

Let’s look at an example.

Say you want to ask people about their bath water temperature preferences. There are many ways you can do this, using a survey or a questionnaire – here are 3 potential options:

• How do you feel about your spouse’s bath water temperature preference? (Qualitative. This open-ended question leaves a lot of space so that the respondent can rant in an adequate manner).
• What is your preferred bath water temperature? (This one’s tricky because most people don’t know or won’t have a thermometer, but this is a quantitative question with a directly numerical answer).
• Most people who have commented on your bath water temperature have said the following (choose most relevant): It’s too hot. It’s just right. It’s too cold. (Quantitative, because you can add up the number of people who responded in each way and compare them).

The answers provided can be used in a myriad of ways, but, while quantitative responses are easily summarised through counting or calculations, categorised and visualised, qualitative responses need a lot of thought and are re-packaged in a way that tries not to lose too much meaning.

Qualitative vs Quantitative Research: Data collection and analysis

The approach to collecting and analysing data differs quite a bit between qualitative and quantitative research.

A qualitative research approach often has a small sample size (i.e. a small number of people researched) since each respondent will provide you with pages and pages of information in the form of interview answers or observations. In our water perception analysis, it would be super tedious to watch the arguments of 50 couples unfold in front of us! But 6-10 would be manageable and would likely provide us with interesting insight into the great bathwater debate.

To sum it up, data collection in qualitative research involves relatively small sample sizes but rich and detailed data.

On the other side, quantitative research relies heavily on the ability to gather data from a large sample and use it to explain a far larger population (this is called “generalisability”). In our bathwater analysis, we would need data from hundreds of people for us to be able to make a universal statement (i.e. to generalise), and at least a few dozen to be able to identify a potential pattern. In terms of data collection, we’d probably use a more scalable tool such as an online survey to gather comparatively basic data.

So, compared to qualitative research, data collection for quantitative research involves large sample sizes but relatively basic data.

Both research approaches use analyses that allow you to explain, describe and compare the things that you are interested in. While qualitative research does this through an analysis of words, texts and explanations, quantitative research does this through reducing your data into numerical form or into graphs.

There are dozens of potential analyses which each uses. For example, qualitative analysis might look at the narration (the lamenting story of love lost through irreconcilable water toleration differences), or the content directly (the words of blame, heat and irritation used in an interview). Quantitative analysis  may involve simple calculations for averages , or it might involve more sophisticated analysis that assesses the relationships between two or more variables (for example, personality type and likelihood to commit a hot water-induced crime). We discuss the many analysis options other blog posts, so I won’t bore you with the details here.

Qualitative vs Quantitative Research: The pros & cons on both sides

Quantitative and qualitative research fundamentally ask different kinds of questions and often have different broader research intentions. As I said earlier, they are different tools for different jobs – so we can’t really pit them off against each other. Regardless, they still each have their pros and cons.

Let’s start with qualitative “pros”

Qualitative research allows for richer , more insightful (and sometimes unexpected) results. This is often what’s needed when we want to dive deeper into a research question . When we want to find out what and how people are thinking and feeling , qualitative is the tool for the job. It’s also important research when it comes to discovery and exploration when you don’t quite know what you are looking for. Qualitative research adds meat to our understanding of the world and is what you’ll use when trying to develop theories.

Qualitative research can be used to explain previously observed phenomena , providing insights that are outside of the bounds of quantitative research, and explaining what is being or has been previously observed. For example, interviewing someone on their cold-bath-induced rage can help flesh out some of the finer (and often lost) details of a research area. We might, for example, learn that some respondents link their bath time experience to childhood memories where hot water was an out of reach luxury. This is something that would never get picked up using a quantitative approach.

There are also a bunch of practical pros to qualitative research. A small sample size means that the researcher can be more selective about who they are approaching. Linked to this is affordability . Unless you have to fork out huge expenses to observe the hunting strategies of the Hadza in Tanzania, then qualitative research often requires less sophisticated and expensive equipment for data collection and analysis.

Qualitative research also has its “cons”:

A small sample size means that the observations made might not be more broadly applicable. This makes it difficult to repeat a study and get similar results. For instance, what if the people you initially interviewed just happened to be those who are especially passionate about bathwater. What if one of your eight interviews was with someone so enraged by a previous experience of being run a cold bath that she dedicated an entire blog post to using this obscure and ridiculous example?

But sample is only one caveat to this research. A researcher’s bias in analysing the data can have a profound effect on the interpretation of said data. In this way, the researcher themselves can limit their own research. For instance, what if they didn’t think to ask a very important or cornerstone question because of previously held prejudices against the person they are interviewing?

Adding to this, researcher inexperience is an additional limitation. Interviewing and observing are skills honed in over time. If the qualitative researcher is not aware of their own biases and limitations, both in the data collection and analysis phase, this could make their research very difficult to replicate, and the theories or frameworks they use highly problematic.

Qualitative research takes a long time to collect and analyse data from a single source. This is often one of the reasons sample sizes are pretty small. That one hour interview? You are probably going to need to listen to it a half a dozen times. And read the recorded transcript of it a half a dozen more. Then take bits and pieces of the interview and reformulate and categorize it, along with the rest of the interviews.

Now let’s turn to quantitative “pros”:

Even simple quantitative techniques can visually and descriptively support or reject assumptions or hypotheses . Want to know the percentage of women who are tired of cold water baths? Boom! Here is the percentage, and a pie chart. And the pie chart is a picture of a real pie in order to placate the hungry, angry mob of cold-water haters.

Quantitative research is respected as being objective and viable . This is useful for supporting or enforcing public opinion and national policy. And if the analytical route doesn’t work, the remainder of the pie can be thrown at politicians who try to enforce maximum bath water temperature standards. Clear, simple, and universally acknowledged. Adding to this, large sample sizes, calculations of significance and half-eaten pies, don’t only tell you WHAT is happening in your data, but the likelihood that what you are seeing is real and repeatable in future research. This is an important cornerstone of the scientific method.

Quantitative research can be pretty fast . The method of data collection is faster on average: for instance, a quantitative survey is far quicker for the subject than a qualitative interview. The method of data analysis is also faster on average. In fact, if you are really fancy, you can code and automate your analyses as your data comes in! This means that you don’t necessarily have to worry about including a long analysis period into your research time.

Lastly – sometimes, not always, quantitative research may ensure a greater level of anonymity , which is an important ethical consideration. A survey may seem less personally invasive than an interview, for instance, and this could potentially also lead to greater honesty. Of course, this isn’t always the case. Without a sufficient sample size, respondents can still worry about anonymity – for example, a survey within a small department.

But there are also quantitative “cons”:

Quantitative research can be comparatively reductive – in other words, it can lead to an oversimplification of a situation. Because quantitative analysis often focuses on the averages and the general relationships between variables, it tends to ignore the outliers. Why is that one person having an ice bath once a week? With quantitative research, you might never know…

It requires large sample sizes to be used meaningfully. In order to claim that your data and results are meaningful regarding the population you are studying, you need to have a pretty chunky dataset. You need large numbers to achieve “statistical power” and “statistically significant” results – often those large sample sizes are difficult to achieve, especially for budgetless or self-funded research such as a Masters dissertation or thesis.

Quantitative techniques require a bit of practice and understanding (often more understanding than most people who use them have). And not just to do, but also to read and interpret what others have done, and spot the potential flaws in their research design (and your own). If you come from a statistics background, this won’t be a problem – but most students don’t have this luxury.

Finally, because of the assumption of objectivity (“it must be true because its numbers”), quantitative researchers are less likely to interrogate and be explicit about their own biases in their research. Sample selection, the kinds of questions asked, and the method of analysis are all incredibly important choices, but they tend to not be given as much attention by researchers, exactly because of the assumption of objectivity.

Mixed methods: a happy medium?

Some of the richest research I’ve seen involved a mix of qualitative and quantitative research. Quantitative research allowed the researcher to paint “birds-eye view” of the issue or topic, while qualitative research enabled a richer understanding. This is the essence of mixed-methods research – it tries to achieve the best of both worlds .

In practical terms, this can take place by having open-ended questions as a part of your research survey. It can happen by having a qualitative separate section (like several interviews) to your otherwise quantitative research (an initial survey, from which, you could invite specific interviewees). Maybe it requires observations: some of which you expect to see, and can easily record, classify and quantify, and some of which are novel, and require deeper description.

A word of warning – just like with choosing a qualitative or quantitative research project, mixed methods should be chosen purposefully , where the research aims, objectives and research questions drive the method chosen. Don’t choose a mixed-methods approach just because you’re unsure of whether to use quantitative or qualitative research. Pulling off mixed methods research well is not an easy task, so approach with caution!

Recap: Qualitative vs Quantitative Research

So, just to recap what we have learned in this post about the great qual vs quant debate:

• Qualitative research is ideal for research which is exploratory in nature (e.g. formulating a theory or hypothesis), whereas quantitative research lends itself to research which is more confirmatory (e.g. hypothesis testing)
• Qualitative research uses data in the form of words, phrases, descriptions or ideas. It is time-consuming and therefore only has a small sample size .
• Quantitative research uses data in the form of numbers and can be visualised in the form of graphs. It requires large sample sizes to be meaningful.
• Your choice in methodology should have more to do with the kind of question you are asking than your fears or previously-held assumptions.
• Mixed methods can be a happy medium, but should be used purposefully.
• Bathwater temperature is a contentious and severely under-studied research topic.

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

You Might Also Like:

It was helpful

thanks much it has given me an inside on research. i still have issue coming out with my methodology from the topic below: strategies for the improvement of infastructure resilience to natural phenomena

Trackbacks/Pingbacks

• What Is Research Methodology? Simple Definition (With Examples) - Grad Coach - […] Qualitative, quantitative and mixed-methods are different types of methodologies, distinguished by whether they focus on words, numbers or both. This…

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

• Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

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.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

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 .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Bhandari, P. (2023, June 22). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved March 31, 2024, from https://www.scribbr.com/methodology/qualitative-research/

Is this article helpful?

Pritha Bhandari

Other students also liked, qualitative vs. quantitative research | differences, examples & methods, how to do thematic analysis | step-by-step guide & examples, what is your plagiarism score.

Quantitative vs Qualitative Data: What’s the Difference?

If you’re considering a career in data—or in any kind of research field, like psychology—you’ll need to get to grips with two types of data: Quantitative and qualitative .

Quantitative data is anything that can be counted or measured ; it refers to numerical data. Qualitative data is descriptive , referring to things that can be observed but not measured—such as colors or emotions.

In this post, we’ll define both quantitative and qualitative data in more detail. We’ll then explore all the key ways in which they differ—from how they are collected and analyzed, to the advantages and disadvantages of each. We’ll also include useful examples throughout.

By the end, you’ll have a clear understanding of the difference between qualitative and quantitative data, and a good idea of when to use which. Want to skip ahead to a specific section? Just use this clickable menu:

• Quantitative vs qualitative data: What are they, and what’s the difference between them?
• What are the different types of quantitative and qualitative data?
• How are quantitative and qualitative data collected?
• Quantitative vs qualitative data: Methods of analysis
• What are the advantages and disadvantages of quantitative vs qualitative data?
• When should I use qualitative or quantitative data?
• Quantitative vs. qualitative data: FAQ
• Key takeaways 

Without further ado, let’s jump in.

1. What is the difference between quantitative and qualitative data?

When it comes to conducting research and data analysis, you’ll work with two types of data: quantitative and qualitative. Each requires different collection and analysis methods, so it’s important to understand the difference between the two.

What is quantitative data?

Quantitative data refers to any information that can be quantified. If it can be counted or measured, and given a numerical value, it’s quantitative data. Quantitative data can tell you “how many,” “how much,” or “how often”—for example, how many people attended last week’s webinar? How much revenue did the company make in 2019? How often does a certain customer group use online banking?

To analyze and make sense of quantitative data, you’ll conduct statistical analyses.

Learn more: What is quantitative data? A complete introduction

What is qualitative data?

Unlike quantitative data, qualitative data cannot be measured or counted. It’s descriptive, expressed in terms of language rather than numerical values.

Researchers will often turn to qualitative data to answer “Why?” or “How?” questions. For example, if your quantitative data tells you that a certain website visitor abandoned their shopping cart three times in one week, you’d probably want to investigate why—and this might involve collecting some form of qualitative data from the user. Perhaps you want to know how a user feels about a particular product; again, qualitative data can provide such insights. In this case, you’re not just looking at numbers; you’re asking the user to tell you, using language, why they did something or how they feel.

Qualitative data also refers to the words or labels used to describe certain characteristics or traits—for example, describing the sky as blue or labeling a particular ice cream flavor as vanilla.

What are the main differences between quantitative and qualitative data?

The main differences between quantitative and qualitative data lie in what they tell us , how they are collected , and how they are analyzed. Let’s summarize the key differences before exploring each aspect in more detail:

• Quantitative data is countable or measurable, relating to numbers. Qualitative data is descriptive, relating to language.
• Quantitative data tells us how many, how much, or how often (e.g. “20 people signed up to our email newsletter last week”). Qualitative data can help us to understand the “why” or “how” behind certain behaviors, or it can simply describe a certain attribute—for example, “The postbox is red” or “I signed up to the email newsletter because I’m really interested in hearing about local events.”
• Quantitative data is fixed and “universal,” while qualitative data is subjective and dynamic. For example, if something weighs 20 kilograms, that can be considered an objective fact. However, two people may have very different qualitative accounts of how they experience a particular event.
• Quantitative data is gathered by measuring and counting. Qualitative data is collected by interviewing and observing.
• Quantitative data is analyzed using statistical analysis, while qualitative data is analyzed by grouping it in terms of meaningful categories or themes.

The difference between quantitative and qualitative data: An example

To illustrate the difference between quantitative and qualitative data, let’s use an example. Imagine you want to describe your best friend. What kind of data might you gather or use to paint a vivid picture?

First, you might describe their physical attributes, such as their height, their hair style and color, what size feet they have, and how much they weigh. Then you might describe some of their most prominent personality traits. On top of that, you could describe how many siblings and pets they have, where they live, and how often they go swimming (their favorite hobby).

All of that data will fall into either the quantitative or qualitative categories, as follows:

Quantitative data:

• My best friend is 5 feet and 7 inches tall
• They have size 6 feet
• They weigh 63 kilograms
• My best friend has one older sibling and two younger siblings
• They have two cats
• My best friend lives twenty miles away from me
• They go swimming four times a week

Qualitative data:

• My best friend has curly brown hair
• They have green eyes
• My best friend is funny, loud, and a good listener
• They can also be quite impatient and impulsive at times
• My best friend drives a red car
• They have a very friendly face and a contagious laugh

Of course, when working as a researcher or data analyst, you’ll be handling much more complex data than the examples we’ve given. However, our “best friend” example has hopefully made it easier for you to distinguish between quantitative and qualitative data.

2. Different types of quantitative and qualitative data

When considering the difference between quantitative and qualitative data, it helps to explore some types and examples of each. Let’s do that now, starting with quantitative data.

Types of quantitative data (with examples)

Quantitative data is either discrete or continuous :

• Discrete quantitative data takes on fixed numerical values and cannot be broken down further. An example of discrete data is when you count something, such as the number of people in a room. If you count 32 people, this is fixed and finite.
• Continuous quantitative data can be placed on a continuum and infinitely broken down into smaller units. It can take any value; for example, a piece of string can be 20.4cm in length, or the room temperature can be 30.8 degrees.

What are some real-world examples of quantitative data?

Some everyday examples of quantitative data include:

• Measurements such as height, length, and weight
• Counts, such as the number of website visitors, sales, or email sign-ups
• Calculations, such as revenue
• Projections, such as predicted sales or projected revenue increase expressed as a percentage
• Quantification of qualitative data—for example, asking customers to rate their satisfaction on a scale of 1-5 and then coming up with an overall customer satisfaction score

Types of qualitative data (with examples)

Qualitative data may be classified as nominal or ordinal :

• Nominal data is used to label or categorize certain variables without giving them any type of quantitative value. For example, if you were collecting data about your target audience, you might want to know where they live. Are they based in the UK, the USA, Asia, or Australia? Each of these geographical classifications count as nominal data. Another simple example could be the use of labels like “blue,” “brown,” and “green” to describe eye color.
• Ordinal data is when the categories used to classify your qualitative data fall into a natural order or hierarchy. For example, if you wanted to explore customer satisfaction, you might ask each customer to select whether their experience with your product was “poor,” “satisfactory,” “good,” or “outstanding.” It’s clear that “outstanding” is better than “poor,” but there’s no way of measuring or quantifying the “distance” between the two categories.

Nominal and ordinal data tends to come up within the context of conducting questionnaires and surveys. However, qualitative data is not just limited to labels and categories; it also includes unstructured data such as what people say in an interview, what they write in a product review, or what they post on social media.

What are some real-world examples of qualitative data?

Some examples of qualitative data include:

• Interview transcripts or audio recordings
• The text included in an email or social media post
• Product reviews and customer testimonials
• Observations and descriptions; e.g. “I noticed that the teacher was wearing a red jumper.”
• Labels and categories used in surveys and questionnaires, e.g. selecting whether you are satisfied, dissatisfied, or indifferent to a particular product or service.

3. How are quantitative and qualitative data collected?

One of the key differences between quantitative and qualitative data is in how they are collected or generated.

How is quantitative data generated?

Quantitative data is generated by measuring or counting certain entities, or by performing calculations. Some common quantitative data collection methods include:

• Surveys and questionnaires: This is an especially useful method for gathering large quantities of data. If you wanted to gather quantitative data on employee satisfaction, you might send out a survey asking them to rate various aspects of the organization on a scale of 1-10.
• Analytics tools: Data analysts and data scientists use specialist tools to gather quantitative data from various sources. For example, Google Analytics gathers data in real-time, allowing you to see, at a glance, all the most important metrics for your website—such as traffic, number of page views, and average session length.
• Environmental sensors: A sensor is a device which detects changes in the surrounding environment and sends this information to another electronic device, usually a computer. This information is converted into numbers, providing a continuous stream of quantitative data.
• Manipulation of pre-existing quantitative data: Researchers and analysts will also generate new quantitative data by performing statistical analyses or calculations on existing data. For example, if you have a spreadsheet containing data on the number of sales and expenditures in USD, you could generate new quantitative data by calculating the overall profit margin.

How is qualitative data generated?

Qualitative data is gathered through interviews, surveys, and observations. Let’s take a look at these methods in more detail:

• Interviews are a great way to learn how people feel about any given topic—be it their opinions on a new product or their experience using a particular service. Conducting interviews will eventually provide you with interview transcripts which can then be analyzed.
• Surveys and questionnaires are also used to gather qualitative data. If you wanted to collect demographic data about your target audience, you might ask them to complete a survey where they either select their answers from a number of different options, or write their responses as freeform text.
• Observations: You don’t necessarily have to actively engage with people in order to gather qualitative data. Analysts will also look at “naturally occurring” qualitative data, such as the feedback left in product reviews or what people say in their social media posts.

4. Quantitative vs qualitative data: methods of analysis

Another major difference between quantitative and qualitative data lies in how they are analyzed. Quantitative data is suitable for statistical analysis and mathematical calculations, while qualitative data is usually analyzed by grouping it into meaningful categories or themes.

Quantitative data analysis

How you analyze your quantitative data depends on the kind of data you’ve gathered and the insights you want to uncover. Statistical analysis can be used to identify trends in the data, to establish if there’s any kind of relationship between a set of variables (e.g. does social media spend correlate with sales), to calculate probability in order to accurately predict future outcomes, to understand how the data is distributed—and much, much more.

Some of the most popular methods used by data analysts include:

• Regression analysis
• Monte Carlo simulation
• Factor analysis
• Cohort analysis
• Cluster analysis
• Time series analysis

You’ll find a detailed explanation of these methods in our guide to the most useful data analysis techniques .

Qualitative data analysis

With qualitative data analysis, the focus is on making sense of unstructured data (such as large bodies of text). Given that qualitative data cannot be measured objectively, it is open to subjective interpretation and therefore requires a different approach to analysis.

The main method of analysis used with qualitative data is a technique known as thematic analysis. Essentially, the data is coded in order to identify recurring keywords or topics, and then, based on these codes, grouped into meaningful themes.

Another type of analysis is sentiment analysis , which seeks to classify and interpret the emotions conveyed within textual data. This allows businesses to gauge how customers feel about various aspects of the brand, product, or service, and how common these sentiments are across the entire customer base.

Traditionally, qualitative data analysis has had something of a bad reputation for being extremely time-consuming. However, nowadays the process can be largely automated, and there are plenty of tools and software out there to help you make sense of your qualitative data. To learn more about qualitative analysis and what you can do with it, check out this round-up of the most useful qualitative analysis tools on the market .

5. What are the advantages and disadvantages of quantitative vs qualitative data?

Each type of data comes with advantages and disadvantages, and it’s important to bear these in mind when conducting any kind of research or sourcing data for analysis. We’ll outline the main advantages and disadvantages of each now.

What are the advantages and disadvantages of quantitative data?

A big advantage of quantitative data is that it’s relatively quick and easy to collect, meaning you can work with large samples. At the same time, quantitative data is objective; it’s less susceptible to bias than qualitative data, which makes it easier to draw reliable and generalizable conclusions.

The main disadvantage of quantitative data is that it can lack depth and context. The numbers don’t always tell you the full story; for example, you might see that you lost 70% of your newsletter subscribers in one week, but without further investigation, you won’t know why.

What are the advantages and disadvantages of qualitative data?

Where quantitative data falls short, qualitative data shines. The biggest advantage of qualitative data is that it offers rich, in-depth insights and allows you to explore the context surrounding a given topic. Through qualitative data, you can really gauge how people feel and why they take certain actions—crucial if you’re running any kind of organization and want to understand how your target audience operates.

However, qualitative data can be harder and more time-consuming to collect, so you may find yourself working with smaller samples. Because of its subjective nature, qualitative data is also open to interpretation, so it’s important to be aware of bias when conducting qualitative analysis.

6. When should I use qualitative or quantitative data?

Put simply, whether you use qualitative or quantitative data (or a combination of both!) depends on the data analytics project you’re undertaking. Here, we’ll discuss which projects are better suited to which data.

Generally, you can use the following criteria to determine whether to go with qualitative data, quantitative data, or a mixed methods approach to collecting data for your project.

• Do you want to understand something, such as a concept, experience, or opinions? Use qualitative data.
• Do you want to confirm or test something, such as a theory or hypothesis? Use quantitative data.
• Are you taking on research? You may benefit from a mixed methods approach to data collection.

You may find that more often than not, both types of data are used in projects, in order to gain a clear overall image—integrating both the numbers side and human side of things.

6. Quantitative vs. qualitative data: FAQ

What are the main differences between qualitative and quantitative research.

Qualitative research is primarily exploratory and uses non-numerical data to understand underlying reasons, opinions, and motivations. Quantitative research, on the other hand, is numerical and seeks to measure variables and relationships through statistical analysis. Additionally, qualitative research tends to be subjective and less structured, while quantitative research is objective and more structured.

What are examples of qualitative and quantitative data?

Examples of qualitative data include open-ended survey responses, interview transcripts, and observational notes. Examples of quantitative data include numerical survey responses, test scores, and website traffic data. Qualitative data is typically subjective and descriptive, while quantitative data is objective and numerical.

7. Key takeaways

Throughout this post, we’ve defined quantitative and qualitative data and explained how they differ. What it really boils down to, in very simple terms, is that quantitative data is countable or measurable, relating to numbers, while qualitative data is descriptive, relating to language.

Understanding the difference between quantitative and qualitative data is one of the very first steps towards becoming a data expert. If you’re considering a career in data, you’ll find links to some useful articles at the end of this post. Had enough theory and want some action? Check out our list of free data analytics courses for beginners , or cut to the chase and simply sign up for a free, five-day introductory data analytics short course .

• A step-by-step guide to the data analysis process
• What is the typical data analyst career path?
• The best data analytics courses in 2022

Qualitative Vs. Quantitative Research — A step-wise guide to conduct research

A research study includes the collection and analysis of data. In quantitative research, the data are analyzed with numbers and statistics, and in qualitative research, the data analyzed are non-numerical and perceive the meaning of social reality.

What Is Qualitative Research?

Qualitative research observes and describes a phenomenon to gain a deeper understanding of a subject. It is also used to generate hypotheses for further studies. In general, qualitative research is explanatory and helps understands how an individual perceives non-numerical data, like video, photographs, or audio recordings. The qualitative data is collected from diary accounts or interviews and analyzed by grounded theory or thematic analysis.

When to Use Qualitative Research?

Qualitative research is used when the outcome of the research study is to disseminate knowledge and understand concepts, thoughts, and experiences. This type of research focuses on creating ideas and formulating theories or hypotheses .

Benefits of Qualitative Research

• Unlike quantitative research, which relies on numerical data, qualitative research relies on data collected from interviews, observations, and written texts.
• It is often used in fields such as sociology and anthropology, where the goal is to understand complex social phenomena.
• Qualitative research is considered to be more flexible and adaptive, as it is used to study a wide range of social aspects.
• Additionally, qualitative research often leads to deeper insights into the research study. This helps researchers and scholars in designing their research methods .

Qualitative Research Example

In research, to understand the culture of a pharma company, one could take an ethnographic approach. With an experience in the company, one could gather data based on the —

• Field notes with observations, and reflections on one’s experiences of the company’s culture
• Open-ended surveys for employees across all the company’s departments via email to find out variations in culture across teams and departments
• Interview sessions with employees and gather information about their experiences and perspectives.

What Is Quantitative Research?

Quantitative research is for testing hypotheses and measuring relationships between variables. It follows the process of objectively collecting data and analyzing it numerically, to determine and control variables of interest. This type of research aims to test causal relationships between variables and provide generalized results. These results determine if the theory proposed for the research study could be accepted or rejected.

When to Use Quantitative Research?

Quantitative research is used when a research study needs to confirm or test a theory or a hypothesis. When a research study is focused on measuring and quantifying data, using a quantitative approach is appropriate. It is often used in fields such as economics, marketing, or biology, where researchers are interested in studying trends and relationships between variables .

Benefits of Quantitative Research

• Quantitative data is interpreted with statistical analysis . The type of statistical study is based on the principles of mathematics and it provides a fast, focused, scientific and relatable approach.
• Quantitative research creates an ability to replicate the test and results of research. This approach makes the data more reliable and less open to argument.
• After collecting the quantitative data, expected results define which statistical tests are applicable and results provide a quantifiable conclusion for the research hypothesis
• Research with complex statistical analysis is considered valuable and impressive. Quantitative research is associated with technical advancements like computer modeling and data-based decisions.

Quantitative Research Example

An organization wishes to conduct a customer satisfaction (CSAT) survey by using a survey template. From the survey, the organization can acquire quantitative data and metrics on the brand or the organization based on the customer’s experience. Various parameters such as product quality, pricing, customer experience, etc. could be used to generate data in the form of numbers that is statistically analyzed.

Data Collection Methods

1. qualitative data collection methods.

Qualitative data is collected from interview sessions, discussions with focus groups, case studies, and ethnography (scientific description of people and cultures with their customs and habits). The collection methods involve understanding and interpreting social interactions.

Qualitative research data also includes respondents’ opinions and feelings, which is conducted face-to-face mostly in focus groups. Respondents are asked open-ended questions either verbally or through discussion among a group of people, related to the research topic implemented to collect opinions for further research.

2. Quantitative Data Collection Methods

Quantitative research data is acquired from surveys, experiments, observations, probability sampling, questionnaire observation, and content review. Surveys usually contain a list of questions with multiple-choice responses relevant to the research topic under study. With the availability of online survey tools, researchers can conduct a web-based survey for quantitative research.

Quantitative data is also assimilated from research experiments. While conducting experiments, researchers focus on exploring one or more independent variables and studying their effect on one or more dependent variables.

A Step-wise Guide to Conduct Qualitative and Quantitative Research

• Understand the difference between types of research — qualitative, quantitative, or mixed-methods-based research.
• Develop a research question or hypothesis. This research approach will define which type of research one could choose.
• Choose a method for data collection. Depending on the process of data collection, the type of research could be determined.
• Analyze and interpret the collected data. Based on the analyzed data, results are reported.
• If observed results are not equivalent to expected results, consider using an unbiased research approach or choose both qualitative and quantitative research methods for preferred results.

Qualitative Vs. Quantitative Research – A Comparison

With an awareness of qualitative vs. quantitative research and the different data collection methods , researchers could use one or both types of research approaches depending on their preferred results. Moreover, to implement unbiased research and acquire meaningful insights from the research study, it is advisable to consider both qualitative and quantitative research methods .

Through this article, you would have understood the comparison between qualitative and quantitative research. However, if you have any queries related to qualitative vs. quantitative research, do comment below or email us.

Well explained and easy to understand.

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for data interpretation

In research, choosing the right approach to understand data is crucial for deriving meaningful insights.…

Demystifying the Role of Confounding Variables in Research

In the realm of scientific research, the pursuit of knowledge often involves complex investigations, meticulous…

Research Interviews: An effective and insightful way of data collection

Research interviews play a pivotal role in collecting data for various academic, scientific, and professional…

Planning Your Data Collection: Designing methods for effective research

Planning your research is very important to obtain desirable results. In research, the relevance of…

• Manuscripts & Grants
• Trending Now

Unraveling Research Population and Sample: Understanding their role in statistical inference

Research population and sample serve as the cornerstones of any scientific inquiry. They hold the…

6 Steps to Evaluate the Effectiveness of Statistical Hypothesis Testing

How to Use Creative Data Visualization Techniques for Easy Comprehension of…

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What should universities' stance be on AI tools in research and academic writing?

• How it works

Qualitative Vs Quantitative Research – A Comprehensive Guide

Published by Carmen Troy at August 13th, 2021 , Revised On September 20, 2023

What is Quantitative Research?

Quantitative research is associated with numerical data or data that can be measured. It is used to study a large group of population. The information is gathered by performing statistical, mathematical, or computational techniques.

Quantitative research isn’t simply based on  statistical analysis or quantitative techniques but rather uses a certain approach to theory to address research hypotheses or questions, establish an appropriate research methodology, and draw findings & conclusions .

Characteristics of Quantitative Research

Some most commonly employed quantitative research strategies include data-driven dissertations, theory-driven studies, and reflection-driven research. Regardless of the chosen approach, there are some common quantitative research features as listed below.

• Quantitative research tests or builds on other researchers’ existing theories whilst taking a reflective or extensive route.
• Quantitative research aims to test the research hypothesis or answer established research questions.
• It is primarily justified by positivist or post-positivist research paradigms.
• The  research design can be relationship-based, quasi-experimental, experimental, or descriptive.
• It draws on a small sample to make generalisations to a wider population using probability sampling techniques.
• Quantitative data is gathered according to the established research questions using research vehicles such as structured observation, structured interviews, surveys, questionnaires, and laboratory results.
• The researcher uses  statistical analysis tools and techniques to measure variables and gather inferential or descriptive data. In some cases, your tutor or dissertation committee members might find it easier to verify your study results with numbers and statistical analysis.
• The study results’ accuracy is based on external and internal validity and authenticity of the data used.
• Quantitative research answers research questions or tests the hypothesis using charts, graphs, tables, data, and statements.
• It underpins  research questions or hypotheses and findings to make conclusions.
• The researcher can provide recommendations for future research and expand or test existing theories.

What is Qualitative Research?

Qualitative research is a type of scientific research where a researcher collects evidence to seek answers to a  question . It is associated with studying human behavior from an informative perspective. It aims at obtaining in-depth details of the problem.

As the term suggests,  qualitative research  is based on qualitative research methods, including participants’ observations, focus groups, and unstructured interviews.

Qualitative research is very different in nature when compared to quantitative research. It takes an established path towards the  research process , how  research questions  are set up, how existing theories are built upon, what research methods are employed, and how the  findings  are unveiled to the readers.

You may adopt conventional methods, including phenomenological research, narrative-based research, grounded theory research, ethnographies, case studies, and auto-ethnographies.

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Characteristics of Qualitative Research

Again, regardless of the chosen approach to qualitative research, your dissertation will have unique key features as listed below.

• The research questions that you aim to answer will expand or even change as the  dissertation writing process continues . This aspect of the research is typically known as an emergent design where the research objectives evolve with time.
• Qualitative research may use existing theories to cultivate new theoretical understandings or fall back on existing theories to support the research process. However, the original goal of testing a certain theoretical understanding remains the same.
• It can be based on various research models, such as critical theory, constructivism, and interpretivism.
• The chosen research design largely influences the analysis and discussion of results and the choices you make . Research design depends on the adopted research path: phenomenological research, narrative-based research, grounded theory-based research, ethnography, case study-based research, or auto-ethnography.
• Qualitative research answers research questions with theoretical sampling, where data gathered from the organisation or people are studied.
• It involves various research methods to gather qualitative data from participants belonging to the field of study. As indicated previously, some of the most notable qualitative research methods include participant observation, focus groups, and unstructured interviews.
• It incorporates an  inductive process where the researcher analyses and understands the data through his own eyes and judgments to identify concepts and themes that comprehensively depict the researched material.
• The key quality characteristics of qualitative research are transferability, conformity, confirmability, and reliability.
• Results and discussions are largely based on narratives, case study and personal experiences, which help detect inconsistencies, observations, processes, and ideas.
• Qualitative research discusses theoretical concepts obtained from the results whilst taking research questions and/or hypotheses to  draw general  conclusions .

Confused between qualitative and quantitative methods of data analysis? No idea what discourse and content analysis are?

We hear you.

• Whether you want a full dissertation written or need help forming a dissertation proposal, we can help you with both.
• Get different dissertation services at ResearchProspect and score amazing grades!

When to Use Qualitative and Quantitative Research Model?

• The research  title, research questions,  hypothesis , objectives, and study area generally determine the dissertation’s best research method.
• If the primary aim of your research is to test a hypothesis, validate an existing theory or perhaps measure some variables, then the quantitative research model will be the more appropriate choice because it might be easier for you to convince your supervisor or members of the dissertation committee with the use of statistics and numbers.
• On the other hand, oftentimes, statistics and a collection of numbers are not the answer, especially where there is a need to understand meanings, experiences, and beliefs.
• If your research questions or hypothesis can be better addressed through people’s observations and experiences, you should consider qualitative data.
• If you select an inappropriate research method, you will not prove your findings’ accuracy, and your dissertation will be pretty much meaningless. To prove that your research is authentic and reliable, choose a research method that best suits your study’s requirements.
• In the sections that follow, we explain the most commonly employed research methods for the dissertation, including quantitative, qualitative, and mixed research methods.

Now that you know the unique differences between quantitative and qualitative research methods, you may want to learn a bit about primary and secondary research methods.

Here is an article that will help you  distinguish between primary and secondary research  and decide whether you need to use quantitative and/or qualitative methods of primary research in your dissertation.

Alternatively, you can base your dissertation on secondary research, which is descriptive and explanatory.

Limitations of Quantitative and Qualitative Research

What is quantitative research, what is qualitative research.

Qualitative research is a type of scientific research where a researcher collects evidence to seek answers to a question . It is associated with studying human behavior from an informative perspective. It aims at obtaining in-depth details of the problem.

Qualitative or quantitative, which research type should I use?

The research title, research questions, hypothesis , objectives, and study area generally determine the dissertation’s best research method.

You May Also Like

Disadvantages of primary research – It can be expensive, time-consuming and take a long time to complete if it involves face-to-face contact with customers.

A survey includes questions relevant to the research topic. The participants are selected, and the questionnaire is distributed to collect the data.

In historical research, a researcher collects and analyse the data, and explain the events that occurred in the past to test the truthfulness of observations.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

An official website of the United States government

The .gov means it's official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Browse Titles

NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Qualitative study.

Steven Tenny ; Janelle M. Brannan ; Grace D. Brannan .

Affiliations

Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2] Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” [5] As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. [5] At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. [2] Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”. [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. [4] It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. [2] It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. [6] Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. [2] For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
• Criterion sampling-selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling-selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research. [13]

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or in combination with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation to not only help generate hypotheses which can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are.  Qualitative research provides researchers with a way to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many different ways, including the criteria for evaluating them. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. The correlating concepts in qualitative research are credibility, transferability, dependability, and confirmability. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept is on the left, and the qualitative concept is on the right:

• Internal validity--- Credibility
• External validity---Transferability
• Reliability---Dependability
• Objectivity---Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid so should qualitative researchers ensure that their work has credibility.  

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple methods of data collection to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable by also interviewing the magician, back-stage hand, and the person who "vanished." In qualitative research, triangulation can include using telephone surveys, in-person surveys, focus groups, and interviews as well as surveying an adequate cross-section of the target demographic.
• Peer examination: Results can be reviewed by a peer to ensure the data is consistent with the findings.

‘Thick’ or ‘rich’ description can be used to evaluate the transferability of qualitative research whereas using an indicator such as an audit trail might help with evaluating the dependability and confirmability.

• Thick or rich description is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was carried out. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data themselves, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original records of information should also be kept (e.g., surveys, notes, recordings).

One issue of concern that qualitative researchers should take into consideration is observation bias. Here are a few examples:

• Hawthorne effect: The Hawthorne effect is the change in participant behavior when they know they are being observed. If a researcher was wanting to identify factors that contribute to employee theft and tells the employees they are going to watch them to see what factors affect employee theft, one would suspect employee behavior would change when they know they are being watched.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens in an unconscious manner for the participant so it is important to eliminate or limit transmitting the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in artificial scenarios and/or with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative research by itself or combined with quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research does not exist as an island apart from quantitative research, but as an integral part of research methods to be used for the understanding of the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is important for all members of the health care team as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research.  Much of the qualitative research data acquisition is completed by numerous team members including social works, scientists, nurses, etc.  Within each area of the medical field, there is copious ongoing qualitative research including physician-patient interactions, nursing-patient interactions, patient-environment interactions, health care team function, patient information delivery, etc. 

• Review Questions
• Access free multiple choice questions on this topic.
• Comment on this article.

Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

In this Page

Bulk download.

• Bulk download StatPearls data from FTP

Related information

• PMC PubMed Central citations
• PubMed Links to PubMed

Similar articles in PubMed

• Suicidal Ideation. [StatPearls. 2024] Suicidal Ideation. Harmer B, Lee S, Duong TVH, Saadabadi A. StatPearls. 2024 Jan
• Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas. [Cochrane Database Syst Rev. 2022] Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas. Crider K, Williams J, Qi YP, Gutman J, Yeung L, Mai C, Finkelstain J, Mehta S, Pons-Duran C, Menéndez C, et al. Cochrane Database Syst Rev. 2022 Feb 1; 2(2022). Epub 2022 Feb 1.
• Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012). [Phys Biol. 2013] Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012). Foffi G, Pastore A, Piazza F, Temussi PA. Phys Biol. 2013 Aug; 10(4):040301. Epub 2013 Aug 2.
• Review Evidence Brief: The Effectiveness Of Mandatory Computer-Based Trainings On Government Ethics, Workplace Harassment, Or Privacy And Information Security-Related Topics [ 2014] Review Evidence Brief: The Effectiveness Of Mandatory Computer-Based Trainings On Government Ethics, Workplace Harassment, Or Privacy And Information Security-Related Topics Peterson K, McCleery E. 2014 May
• Review Public sector reforms and their impact on the level of corruption: A systematic review. [Campbell Syst Rev. 2021] Review Public sector reforms and their impact on the level of corruption: A systematic review. Mugellini G, Della Bella S, Colagrossi M, Isenring GL, Killias M. Campbell Syst Rev. 2021 Jun; 17(2):e1173. Epub 2021 May 24.

Recent Activity

• Qualitative Study - StatPearls Qualitative Study - StatPearls

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

Connect with NLM

National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894

Web Policies FOIA HHS Vulnerability Disclosure

Help Accessibility Careers

Cookie consent

We use our own and third-party cookies to show you more relevant content based on your browsing and navigation history. Please accept or manage your cookie settings below. Here's our   cookie policy

• VideoAsk Video-enhanced forms
• Formless AI-powered forms
• Form builder Signups and orders
• Survey maker Research and feedback
• Quiz maker Trivia and product match
• Find customers Generate more leads
• Get feedback Discover ways to improve
• Do research Uncover trends and ideas
• Marketers Forms for marketing teams
• Product Forms for product teams
• HR Forms for HR teams
• Customer success Forms for customer success teams
• Business Forms for general business
• Form templates
• Survey templates
• Quiz templates
• Poll templates
• Order forms
• Feedback forms
• Satisfaction surveys
• Application forms
• Feedback surveys
• Evaluation forms
• Request forms
• Signup forms
• Business surveys
• Marketing surveys
• Report forms
• Customer feedback form
• Registration form
• Branding questionnaire
• 360 feedback
• Lead generation
• Contact form
• Signup sheet
• Google Sheets
• Google Analytics
• ActiveCampaign
• Help center Find quick answers
• Contact us Speak to someone
• Our blog Get inspired
• Our community Share and learn
• Our guides Tips and how-to
• Updates News and announcements
• Partners Browse or join
• Careers Join our team
• → Qualitative vs. quantitative research...

Qualitative vs. quantitative research: A simple guide

Quantitative research deals with numbers and statistics, while qualitative research involves pulling information from experiences and stories.

Latest posts on Tips

Typeform    |    03.2024

From Tesla to Tushy, every successful brand is built on a foundation of both quantitative and qualitative research. Marketers and product developers use this zero-party data to frame their advertising strategies, product positioning, and brand voice—basically, everything that goes into designing and selling a product or service.

When it comes to qualitative vs. quantitative research, both methods have their benefits and drawbacks in certain applications. We break down what you need to know before running your next round of market research. 

Qualitative vs. quantitative research: What’s the difference?

Quantitative research counts and measures numbers to find statistical patterns, while qualitative research is a deep dive into understanding people’s thoughts and experiences. They're similar in that they both aim to uncover valuable insights, but they use different tools and approaches to do so.

But don’t be fooled into thinking that one research method is better than the other—both require systematically applied research methods and analysis.

What is qualitative research and data?

Qualitative research is like the Sherlock Holmes of the research world—it seeks to uncover the hidden stories, motivations, and intricacies that numbers can't reveal. Instead of crunching data, it dives deep into people's experiences, thoughts, and feelings to help explain certain behaviors and patterns. 

In qualitative research, it's not about numbers but rather words, pictures, and observations. You'll collect rich, unstructured data via interviews, focus group discussions, or open-ended surveys. 

Say you're a marketing rep keen on understanding how people perceive your smartphone brand. 

First, you organize a series of in-depth interviews with smartphone users, asking open-ended questions about their experiences with the brand. Participants share stories about their interactions, likes, dislikes, and emotional connections with the product. You also delve into social media posts, online reviews, and forum discussions to gauge the brand's online reputation.

As you analyze this data, patterns begin to emerge. You find that users consistently describe the brand as "innovative" and "user-friendly." However, you also discover a recurring frustration with battery life and customer support. Qualitative research not only provides you with insights into how people perceive the brand but also dives into the emotional nuances behind their perceptions. Armed with this knowledge, you can fine-tune your advertising campaigns and product improvements to align with your target audience's genuine feelings and experiences.

Pros and cons of qualitative research

Qualitative research is your go-to when you want to explore the human side of data. It's like having a heart-to-heart conversation with your research subjects. Just keep in mind that, like any detective work, it comes with its own quirks and challenges.

Deep insights: It's great at uncovering the "whys" and "hows" behind human behavior, providing rich insights that quantitative data can miss.

Flexible and exploratory: Qualitative research allows for flexibility, so you can adapt your questions and approach when you face the unexpected.

Humanizing data: Unlike numbers, qualitative research humanizes data by bringing stories and personal experiences to the forefront. It's perfect for capturing human nuances and emotions.

Subjectivity: Different researchers might draw different conclusions from the same data based on their own personal feelings, experiences, or opinions, so it's crucial to stay aware of potential bias.

Resource-intensive: Qualitative research demands time and effort. Conducting interviews, transcribing, and analyzing data is a labor-intensive process, which might not suit all budgets or timelines.

Smaller samples: Your pool of participants tends to be smaller compared to quantitative research, making it challenging to generalize findings to a larger population. It's like diving deep into a few personal stories rather than looking at the bigger picture.

Can’t always be automated: Unlike quantitative research, where you can automate data collection and analysis with software, qualitative research relies heavily on human interaction and interpretation. You can, however, create a survey with open-ended questions to collect qualitative data. Better yet, try our VideoAsk feature, which allows you to ask questions via pre-recorded video and lets respondents answer in video, voice, or text format, preserving that ever-important human element that defines qualitative data. 

What is quantitative research and data?

Quantitative research is all about numbers, statistics, and cold, hard data. It’s more structured and objective and helps reduce researcher biases . It gets at the “what” of a person’s behavior by answering questions like how many, how often, and to what extent?

Let’s look at quantitative research in action. Imagine you're trying to pinpoint the target market for your new fitness app. You survey the app's users, collecting data on their age, gender, location, and fitness habits. The data reveals that 75% of your target users are ages 18-34, with a nearly even split between men and women. You also notice that users in urban areas are 20% more likely to use your app regularly than those in rural areas.

Quantitative research doesn't stop at just counting, though. It's also about analyzing data to spot trends and differences. In this case, it's clear that your core audience consists of younger adults in urban settings, and you can tailor your marketing strategies and app features to better cater to this demographic. So, if you're a number-crunching, stats-loving kind of researcher, quantitative research is your jam.

Pros and cons of quantitative research

In a nutshell, quantitative research is your go-to when you want solid, numerical answers. But remember, it won't tell you the whole story, and sometimes, life's questions are a bit too complex for a numbers-only approach. Keep these pros and cons in mind when running your next quantitative study:

Precision with numbers: Quantitative research is like a laser-guided missile for numbers. It offers precise measurements and statistical analysis, which is great when you need concrete answers.

Reproducibility: It's a cookie-cutter approach—your methods and results can be replicated by others, making it a cornerstone of scientific rigor.

Generalizability: You can often apply findings to a larger population—if it works for one group, it might work for a similar one.

Limited bias: Quantitative research can be a bias-buster. With structured surveys, standardized data collection methods, and statistical analysis, it's easier to minimize researcher bias and keep the study objective. 

Fewer resources: If you're watching your budget, quantitative research may give you more bang for your buck. It often requires fewer resources in terms of time, personnel, and money, making it a practical choice, especially for smaller-scale research projects.

Limited depth: While it's king of numbers, quantitative research can be a bit shallow in understanding. It's like knowing the “what” but not the “why.”

Context ignored: Sometimes context gets lost in a sea of numbers, and you might miss the bigger picture.

Inflexibility: If your research question isn't easily quantifiable, you might end up with results that are difficult to decipher. Not everything can be counted or measured.

Which is better: Qualitative or quantitative research?

It’s a trick question. We’re not pitting qualitative and quantitative research against each other. However, one may prove more useful than the other, depending on your research goals. 

For example, it’s best to stick with qualitative research when:

You want to explore in-depth: Choose qualitative research when you need a deep understanding of a complex phenomenon, like customer perceptions or human behavior. It's like peeling back the layers of an onion to uncover the core.

You need to generate hypotheses: Qualitative research is fantastic for generating ideas or hypotheses that you can later test with quantitative research. 

You value the human perspective: If you want to capture emotions, stories, and personal experiences, opt for qualitative research. It's your go-to when you're interested in "the why" rather than just "the what."

On the other hand, quantitative research may prove more valuable if:

You need to measure and quantify: If you're after hard numbers, like percentages, averages, or correlations, quantitative research is your go-to.

You want to generalize to a larger population: Quantitative research allows you to make statistically valid generalizations to a broader audience. If you plan to reach a wide market, this is your best bet.

You prefer structured and standardized data collection: When consistency and minimizing bias are critical, quantitative research methods like surveys and online tests provide a structured and uniform approach. 

However, you aren’t limited to just one type of research method. You can use both qualitative and quantitative data to give you the most insightful information when:

You need a comprehensive understanding: Sometimes, using both qualitative and quantitative research sequentially is the ideal approach. Start with qualitative research to explore a topic, identify key variables, and generate hypotheses. Then, use quantitative research to test those hypotheses on a larger scale, ensuring a more comprehensive understanding.

You want to validate findings: When you've conducted qualitative research and want to make sure your findings are not just anecdotal, quantitative research can validate and generalize your insights to a broader population.

You're tackling a complex problem: For multifaceted issues, using both approaches can provide a well-rounded view. Qualitative research can uncover the depth and nuances, while quantitative research can quantify the extent of the issue and help prioritize actions.

Quantitative research provides evidence and predictions. Qualitative research provides context and explanations. So which one is best for you? That depends on the questions you need answered.

Research methods

Quantitative and qualitative research methods are systematic ways of collecting data and testing hypotheses. And guess what? It’s something you already do all the time.

We constantly take in information from our surroundings to figure out how to interact with the people around us.

The same goes for market research . A company tries to learn more about their customers and the market. Why? To develop an effective marketing plan or tweak one they already have. The method you use to do this depends on the data that will answer your key questions.

Qualitative research methods

Here are some of the most common qualitative research methods:

In-depth interviews: Known as IDI in market research circles, in-depth interviews are ideal for digging into people’s attitudes and experiences. 

Case studies: In-depth analysis of a single case or a few cases are best suited for investigating unique or complex cases in depth

Focus groups: These are effective for getting several opinions in a conversational format. Participants lead the discussion, while a facilitator guides the conversation through a list of topics, questions, or projective exercises.

Participant observation: Simply engaging and observing your audience day-to-day provides a firsthand view of how people interact in real-life situations.

Historical research: Exploring historical documents and records helps you examine the past through primary and secondary sources, contributing to our understanding of historical events and trends and how they may relate to the current scenario.

Qualitative surveys: Surveys comprised of open-ended questions provide an automated way to receive qualitative data through a quantitative approach..

Ethnography: Ethnography is a broad market research approach that involves all of the methods above in order to gain a comprehensive understanding of the culture or community being studied. 

Quantitative research methods

Here are some of the most common quantitative research methods:

Surveys: Surveys conducted online, over the phone, and even in person with structured interview questionnaires are an efficient way of collecting data from a large pool of participants. 

Polls: Polls are one- or two-question surveys that are often used to gauge public opinion on an important matter (or a frivolous matter—it’s your poll). Because polls are only one or two questions, analysis is pretty much immediate.

Structured observation: This is a structured form of ethnography used to measure certain actions or behaviors, such as tracking how many boxes of cereal people pick up before choosing one to purchase.

Experiment: Market researchers conduct controlled, manipulated, or randomized experiments to understand how specific variables influence outcomes through methods like A/B testing or pilot testing.

Quizzes: Answering a few general questions to find out which Harry Potter character you are may seem like fun and games, but interactive quizzes are a great tool for gathering information while keeping your audience engaged. 

Secondary data analysis: This cost-effective research method taps into big existing datasets like government databases or company records to pull relevant data. 

Mixed research methods

Mixed research methods combine both qualitative and quantitative approaches to provide a comprehensive understanding of the question at hand. Some of the most common mixed research methods include:

User testing: You’ve heard the phrase “Show, don’t tell.” So rather than asking people to explain their experiences, why not have them show you? User testing can tell you where you thrive and fall short, so you can adjust your marketing strategy accordingly.

Help transcripts: Live chat or call transcripts can yield both qualitative and quantitative data. Reading and coding them can help you understand people’s pain points and challenges throughout your conversion funnel.

Customer reviews: Look beyond your own surveys and check sites like Yelp or Google reviews. What are people saying about you? What do they like and dislike? The things people say and how often they say it can yield robust qualitative and quantitative data.

Data analysis

Data analysis is the search for patterns in data, followed by the interpretation of that information to help explain why those patterns are there.

It’s important to keep in mind that quantitative and qualitative data aren't mutually exclusive.

Qualitative data can be translated into quantitative data. For example, you could count the number of times interviewees used a particular word to describe your product to yield quantitative data.

Similarly, quantitative methods of analysis require you to explain what the patterns mean and connect them to other parts of your business—a qualitative exercise!

Qualitative data analysis example

Qualitative data can be difficult to analyze since it’s largely made up of text, images, videos, and open-ended responses instead of numbers. Examples of qualitative data analysis include:

Thematic analysis: Identifying and categorizing recurring themes, patterns, or concepts within the data to uncover the most prevalent and significant themes in your dataset

Content analysis: Examining large amounts of text, visuals, or audio content to identify themes or patterns 

Discourse analysis: Dissecting the language used in the data to understand how individuals or groups construct meaning and social reality through their discourse

Cross-case analysis: Comparing and contrasting multiple cases to identify commonalities and differences, helping to develop broader insights

Quantitative data analysis example

Quantitative data analysis is all about crunching numbers. It can involve presenting data models such as graphs, charts, tables, probabilities, and more.

Tools like Excel, R, and Stata make it easy to track quantitative data like:

Average scores and means

The number of times a specific response is recorded

Connections or potential cause-and-effect relationships between two or more variables

The reliability and validity of results 

Get the right data with Typeform

Congrats—you’ve learned all about the differences between qualitative vs. quantitative research.

Now, the key to successful data collection is iteration.

That doesn’t mean doing the same thing again and again.

It means continually returning to your questions, methods, and data to spark new ideas and insights that'll level up your research —and your business.

Typeform makes it easy to design and automate forms that collect both quantitative and qualitative data—no extensive interviews or focus groups required. With conditional formatting and various question types, you can gather the information you need to get more customers.

About the author

Lydia is an endlessly curious brand and content marketer with a fervor for writing. Find her over at the Typeform blog or sauntering around the PNW.

Liked that? Check these out:

Design tips for non-designers by Hey Studio and Typeform

Verònica Fuerte of Hey Studio and our own designers offer six simple tips for anyone trying to create beautiful design.

Maite Mugica    |    08.2020

What is brand perception? How to measure and improve it

Survey School 4: Survey Analysis 101

Surveys are a great way to gain insights to help answer questions. But to get to making a decision, we first need to perform survey analysis. We've made survey analysis simple with our guide on transforming survey results into actionable insights.

Typeform    |    05.2023

Qualitative vs. quantitative research

While the topic of qualitative vs. quantitative research may sound intimidating, they’re easy concepts to understand, and they represent things that you’re probably doing already. No matter your industry, most business professionals want to get customer feedback and know their audience , whether you call it research or something else.

First things first, suggesting that qualitative and quantitative research are at odds with one another is misleading. While quantitative research is the method that most people are familiar with (and the one that gets all the credit), the two complement each other fundamentally. Together, they can give a more holistic view of a problem or situation. Having one without the other means that you’re only getting half the story. Both play a valuable role in measuring your customer experience .

For example, after a sizable European car rental company spent time and money developing a car rental subscription membership on a hunch, they were stumped by its poor performance. First, analytics showed that users saw the ads but didn’t sign up. Then, after getting feedback from a handful of users, it became painfully clear why no one wanted to belong to the exclusive club.

Watch Kate Margolis, UX/UI Design Lead at Thirdfort, tell the story.

Thanks to both qualitative and quantitative research, the team changed the membership value proposition to boost its desirability for potential users—leading to a 65% conversion of membership after only being asked once.

While there are significant differences between qualitative and quantitative research methods, it’s essential to understand the benefits and blind spots. So let’s start with quantitative research.

What is quantitative research?

Quantitative research is the process of collecting and analyzing numerical data. It aims to find patterns and averages, make predictions, test causal relationships, and generalize results to broader populations by representing data expressed as numbers.

Quantitative research is unlike qualitative research in one critical aspect—it’s numerical. This is because the output of quantitative research is numbers and statistics.

How UserTesting can help you conduct quantitative research methods

The following features, which are popular ways of conducting quantitative research, are all available on the UserTesting platform.

1. Surveys (ratings, ranking, scales, and closed-ended questions)

Not all surveys have to be taken silently. Our customers can customize surveys, hosted on third-party tools like Survey Monkey, for example, and ask contributors to speak aloud and offer reasoning as they answer questions. Not sure when to use them? At UserTesting, they’re commonly done before development, during the design process, or after a product launch.

2. A/B testing

Suitable for product managers and marketers alike, this method tests two options to see which comes out on top. To ensure quality results and prevent do-overs, get a feel for customers’ preferences and even get qualitative feedback before deciding on what to test. When creating the test, it’s always best to over-communicate any questions to better understand why contributors prefer one design over another.

A major pediatric health system came to UserTesting to transform its website and apps, aiming for a more customer-focused experience. Using A/B testing , the team showed contributors multiple homepage image options and dove into why some were preferred over others. Contributors’ feedback showed that there was a strong preference for photos with real patients over stock images, and the team’s digital marketers were able to share this confidently to stakeholders.

3. Benchmarking

You may know all too well that a website or app is never fully done. As the market and customers’ needs evolve, so must our work. Whether your product launched for the first time, or for the 20th, benchmark studies are a way to assess how your product’s experience has changed over months or years. The results historically document how redesigns and changes are perceived by contributors and how competitors stack up. Consider launching these tests before committing to any serious redesign efforts, and keep it focused, whether you’re targeting the overall user experience or a specific feature.

4. Web analytics

UserTesting offers a variety of analytics tools that display contributors’ screen interactions, customer behaviors, keyword maps, positive or negative sentiments, and more. These tools will help track where users tend to click on a screen, offer a glimpse of where you should dig deeper, highlight common behaviors, and showcase any pain points among others. This helps cut down on any manual effort you might have spent pinpointing and organizing data.

Advantages and disadvantages of quantitative data

What’s excellent about quantitative data is that you can easily replicate it. Quantitative data collection is relatively easy to do, and so is analysis. Since you’re dealing with numbers, it’s typically easier to interpret quantitative data and present your findings to others in a less subjective way.

It’s human nature to trust numbers. We tend to believe they’re concrete. Quantitative methods get more attention because it’s easier to tie quantitative measurements to performance metrics and ROI. But unfortunately, there are many ways numbers can be unreliable.

While numerical data can tell you that there’s a problem, it seldom tells you why. Plus, by focusing on numbers only, there’s a risk of missing a factor or common denominator.

Here are some examples where quantitative data isn’t enough information to make an informed decision:

• An e-commerce agency notices that her client’s shoppers are dropping off on one of their biggest channels before reaching checkout, but they don’t know why.
• A product manager is getting survey data showing that new customers are not satisfied with the onboarding process. While she has an idea of what it could be, she’s not sure where to start.
• A marketing team spent weeks developing and rolling out a campaign that flopped. While the team believes they’re on the right track, the President of the company, who never liked the idea, tells them to abandon it altogether.

As you can see from the examples, quantitative data only gives you half of what you need before you can move forward. Lastly, a significant drawback to quantitative research is that numbers don’t convey stories well. So while it’s easy to share a table of data points with an audience, it’s harder to get them to absorb the information and remember it later.

What is qualitative research?

Qualitative research is a behavioral research method that relies on non-numerical data derived from observations and recordings that approximate and characterize phenomena. It’s collecting, analyzing, and interpreting non-numerical data, such as language. It sometimes seeks to understand how an individual subjectively perceives and gives meaning to their social reality.

Instead of numbers, qualitative data comes from studying subjects in their natural environment and focusing on understanding the why and how of human behavior in a given situation. It’s especially effective in obtaining information about people's values, opinions, and behaviors. At UserTesting, qualitative data is collected through contributor observation and interviews.

How UserTesting can help you conduct qualitative research

Researchers, marketers, product managers, and more conduct qualitative research daily using moderated or unmoderated testing with UserTesting. With our platform, business professionals can have access to qualitative data at the speed of quantitative analysis. These are three common qualitative research methods:

1. Contributor observation

Observing and listening is the core of UserTesting’s platform. Whether you’re conducting a moderated or unmoderated test, observing our contributors to obtain their feedback is vital to improving or redesigning your product. We recommend keeping your questions neutral to prevent swaying any feedback, over-communicating your ask (without bias), and letting the contributor take the lead as they complete the tasks.

For a use case idea, consider optimizing in-person experiences by watching your customers record themselves in a new store or at home—known as an ethnography study . This type of study can highlight how contributors, using rear-facing cameras, have something set up or stored in their home and how they live day-to-day and make decisions. For example, REI relied on UserTesting to better understand various types of buyers and supporters. Using light ethnography studies, REI asked contributors to show how they stored their REI equipment and discuss how long they’ve had them. As for the result? REI became more efficient in testing the right demographic for future studies.

2. In-depth or unstructured interviews

In-depth interviews are optimal for collecting data on individuals’ personal histories, perspectives, and experiences, mainly when exploring sensitive topics or follow-up questions are likely necessary. When asking open questions, the interviewer can get a real sense of the person’s understanding of a situation. For example, they might say one thing, but their body language says something else. You may decide on this method to create better solutions and experiences by exploring your users' attitudes, preferences, and opinions as they test out designs and prototypes.

3. Focus groups

Focus groups are what you may consider a “group brainstorm”—when a moderator effectively gathers information from multiple subjects at once and generates broad overviews of issues or concerns related to the demographics represented. These offer a lot of flexibility, and can be done in person or online. Here at UserTesting, focus groups can consist of up to three or five contributors and while they may be less thorough compared to our 1-on-1 Live Conversations , you’ll get a real time look about multiple people’s thoughts and actions—and how they differ.

Though these can be conducted at any time during a product’s life cycle, we recommend setting these up before design development, before you have limited time and budgets on the line.

Advantages and disadvantages of qualitative data

The most significant advantage to qualitative data is that it’s easy to present your data as a story to your audience. In this way, qualitative data has both staying power and the ability to persuade others. People remember stories and how they make them feel. While charts and numbers can convince others to change, they won’t always translate into action or follow-through. One of qualitative data’s biggest advantages is that it offers rich, in-depth insights that allow you to explore new contexts and deeper understandings.

The drawbacks of qualitative research are that it’s often not a statistically representative form of data collection, and it can require multiple data sessions, which can lead to varying analyses and a lot of time and resources spent

Examples of qualitative vs. quantitative research questions

When planning research, you want to be strategic with your test questions. Here are some examples of qualitative vs. quantitative questions to give you a better idea of what to ask.

Quantitative research questions

Quantitative research questions are typically set up so that the answer is numerical or statistical or so that the answer is objective. Typically, this process is automated and answers can’t be followed by more questions.

• How long have you been a customer of our organization?
• On a scale of 1-5, how likely are you to purchase our products again?
• How often do you drink coffee at home?
• Do you prefer to watch movies at home or in the theater ?

Qualitative research questions

Qualitative research questions are open-ended. The interviewer can react to answers and probe for more detail.

• What does the app need to do to improve your experience?
• Do you have any comments, questions, or concerns about our website?
• What do you like most about your favorite coffee shop?
• What did you like about this movie?

Why you need both qualitative and quantitative research

Most importantly, the intersection of quantitative and qualitative data methodologies is where human insights come to life. Both methods can be helpful, but combined, they allow you to see things you may have missed.

According to Justin Wei, Former Head of Digital Marketing at Royal Wins, while quantitative data is the black and white picture of a problem or opportunity, qualitative data can color your understanding.

Quantitative data is 'the what' and qualitative data is 'the why'

Commonly, quantitative data will surface trends that you can use as a springboard for qualitative research. However, it’s important to use qualitative research to drive innovation. Organizations that fall into the habit of only using qualitative research to react to quantitative data run the risk of reducing team efficiency and restricting their ability to optimize.

In general, here are some common reasons to use qualitative research or quantitative research:

• Validate hypotheses: quantitative research will get you the key performance indicators (KPIs) you need when you need objective information to confirm or disprove your theory.
• Find answers: It’s typically easier and less expensive to have people fill out a survey than participate in a focus group. In this way, quantitative methods can help answer questions like: were you satisfied with your experience? Would you recommend us to a friend? On the other hand, qualitative research enables you to respond to open-ended questions like: why were you satisfied with your experience? Why would you recommend us to a friend?
• Uncover emotion: qualitative research is especially good at uncovering the emotions behind data. This can be verbal, body language, or facial expressions caught on video. It helps to hear and see your customers describe wants, needs, concerns, frustrations, etc. Qualitative data will get you that.

Watch Jonathan Greenblatt, User Research and Design Leader, explain how WarnerMedia uses quantitative and qualitative research to flesh out its user personas.

Want to learn more?

Bring customer perspectives into more decisions across teams and experiences to design, develop, and deliver products with more confidence and less risk. 

Not finding what you’re looking for?

Try one of these queries instead:

• Qualitative vs Quantitative Research: When to Use Each

User research is crucial for understanding the needs, preferences, and behaviours of your users. By directly engaging with and observing real users, you gain invaluable insights that can inform the design and development of your product or service.

There are two main approaches to conducting user research: qualitative and quantitative.

This article will provide an overview of qualitative vs quantitative research. I’ll define what each method is, walk through example scenarios of when you might use one versus the other, highlight the benefits of each, and offer guidelines on when qualitative or quantitative user research is most appropriate.

With a foundational understanding of these two complementary research approaches, you’ll be equipped to choose the right user research method(s) for gaining the insights you need.

Let’s get started.

Table of Contents

What is user research.

User research is the study of target users and their needs, goals, and behaviours. It provides critical insights that inform the design and development of products, services, and experiences.

The goal of user research is to understand users’ motivations and thought processes so that solutions can be crafted to meaningfully address their pain points and desires. Researchers utilize various qualitative and quantitative techniques to uncover users’ attitudes, perceptions, and needs.

The findings from user research drive design decisions, product strategy, and business objectives. By grounding designs in real user data, teams can create solutions that delight users by meeting their needs. User research provides a profound understanding of the problem space so that products resonate with users’ mental models and workflows.

Qualitative User Research

Qualitative user research is a set of exploratory research techniques focused on developing a deep understanding of why and how people behave, think, feel, and make decisions. 

It typically involves open-ended observations, interviews, and analysis based on small sample sizes. 

The goal is to uncover insights into human motivations, attitudes and needs through immersive and conversational research methods. 

Rather than focusing on quantitative metrics or measurements, qualitative user research aims to understand the nuanced human context surrounding products, services, and experiences.

Key characteristics of qualitative research include:

Asking open-ended questions – 

Qualitative research utilizes flexible, open-ended questions that allow users to provide thoughtful and descriptive responses. Questions focus on the “why” and “how” behind bbehaviours not just surface-level preferences. For example, researchers may ask “Can you walk me through how you accomplished that task?” rather than “Did you find that task easy or difficult?”. Open questions lead to deeper psychological insights.

Small but focused sample sizes – 

Qualitative studies recruit a smaller number of users, but they represent the target audience segment. For example, rather than 500 broadly targeted surveys, qualitative research may study 8-12 users who match the persona. Smaller samples enable more time spent discovering each user’s nuanced perspectives.

Naturalistic observations – 

Qualitative research observes users interacting in real environments, like their homes or workplaces. This naturalistic approach reveals authentic behaviours versus what people say. Researchers can shadow users and see real-world contexts.

Immersive techniques – 

Qualitative research utilizes ethnography-inspired techniques. Researchers embed themselves alongside users to empathize with their worldview. In-depth interviews, diary studies, and field visits all facilitate first-hand experience of the user’s journey – Through open and natural dialogue, qualitative research uncovers emotional and social insights difficult to extract via surveys or analytics. The human-to-human approach highlights feelings, relationships, and unarticulated needs.

Common Qualitative Research Methods

1. one-on-one interviews.

Conducting a one-on-one user interview involves an in-depth, conversational session between the researcher and a single user representative of the target audience. The interviewer guides the discussion using flexible, open-ended questions to elicit deep insights into the user’s perspectives, bebehavioursand needs.

One-on-one interviews shine when:

• Granular insights are needed from individuals based on their distinct circumstances and backgrounds.
• Understanding nuanced personal contexts, thought processes, pain points and emotions is critical.
• Users may be more forthcoming when peaking alone versus groups.
• The order and wording of questions benefit from real-time adaptation to the dialogue flow.
• Non-verbal cues and body language provide additional context to verbal answers.

Effective one-on-one interview tips include:

• Establishing rapport helps the user open up honestly. Avoid an interrogation vibe.
• Adapt questions based on responses, probing for richer details. Don’t just stick to a rigid script.
• Remain neutral and avoid leading questions that influence the user’s answers.
• Listen fully not just for what’s said but also what’s unspoken. Note emotions and inconsistencies.
• Thank the user for generously providing their time and perspectives. They feel valued.

One-on-one engagement allows deep discovery of individual motivations and contexts. It requires planning, active listening, and interpreting both verbal and non-verbal cues.

2. Focus Groups

A focus group brings together 6-12 users from the target audience for a moderated, interactive discussion focused on a product, service, or topic. Participants share perspectives and build on each other’s ideas in a conversational setting.

Focus groups are advantageous when:

• Real-time user interaction and feedback on concepts is desired.
• Sparking new ideas across users with different attitudes and behaviors is the goal.
• Observing how users influence each other reveals social dynamics and norms.
• A wider range of feedback is needed in the time available versus 1-on-1 interviews.

Tips for productive focus groups include:

• Recruit users who offer diverse perspectives but fit the target audience.
• Use a skilled, neutral moderator to facilitate constructive discussion and keep it on track.
• Explain ground rules upfront so all participants engage respectfully.
• Guide the flow from general to specific questions, leaving time for open discussion.
• Change up activities and stimuli (images, prototype demos) to sustain energy.
• Send recordings for further analysis of responses, interactions, and nonverbal behaviors.

3. User Diaries

User diaries involve having target audience members self-document and reflect on their experiences related to a product or service over time in an ongoing journal. Diary studies provide rich, longitudinal insights from the user’s perspective.

Diary studies are advantageous when:

• Capturing detailed, nuanced accounts of user journeys, motivations, pain points, and perceptions in a real-world context is needed.
• Users are geographically dispersed making direct observations or interviews impractical.
• Revealing changes over time rather than one-off interactions is the research goal.
• Users can clearly articulate their experiences through written or multimedia diaries.

Tips for productive diary studies include:

• Provide clear instructions and templates detailing what details to capture in diary entries over the study duration. Offer tools like written journals, audio recorders, or online forms.
• Set reasonable time commitments per day/week and study length based on depth required and user willingness.
• Check-in throughout the process to maintain participation, answer questions, and fix issues.
• Incentivize participation by compensating users for time spent journaling.
• Regularly review entries to identify compelling patterns and follow up for more context.
• Analyze entries to uncover key themes, insights, and opportunities related to the research aims.

Well-designed diary studies generate rich qualitative data by tapping into users’ direct experiences in their own words over time.

4. Ethnographic Studies

This involves immersing in users’ real-world environments to observe behaviors, understand contexts, and uncover unarticulated needs. Researchers embed directly in the user experience.

Ethnographies excel when:

• Deep insight into “unsaid” user behaviors, motivations, and pain points is needed.
• Directly observing users interacting in real environments provides more authenticity than interviews.
• Longer-term immersion reveals ingrained habits, rituals, and relationships.
• Users cannot fully or accurately articulate their own behaviors and motivations.

Tips for effective ethnographies:

• Clearly define the cultural/environmental scope for observations. Get necessary access.
• Utilize fly-on-the-wall observation techniques to avoid disrupting natural behaviors.
• Take comprehensive notes on user activities, interactions, tools, and environmental factors.
• Look for patterns in activities, conversations, rituals, artifacts, and relationships.
• Balance active observation with informal interview discussions to add context.
• Keep the human perspective; focus on empathy not just data gathering.

5. User Testing

User testing involves directly observing representative users interact with a product or prototype to identify usability issues and collect feedback. Participants work through realistic scenarios while researchers analyze successes, pain points, emotions, and verbal commentary.

User testing shines when:

• Feedback is needed on whether designs meet user expectations and needs.
• Identifying issues in workflows, navigation, learnability, and comprehension is important.
• Directly observing user behavior provides more reliable insights than what they self-report.
• Testing with iterations is built into the product development process.

Tips for effective user testing:

• Develop realistic usage scenarios and test scripts tailored to key research questions. Avoid bias.
• Recruit users matching target demographics and familiarity with the product domain.
• Set up comfortable testing spaces and moderation that put users at ease.
• Record sessions to capture insights from body language, tones, facial expressions etc.
• Analyze results for trends and outliers in behaviors, problems, emotions. Focus on learning.
• Iterate on solutions based on insights. Retest with new users to validate improvements.

6. Think-Aloud-Protocol

The think-aloud protocol method asks users to continuously verbalize their thoughts, feelings, and opinions while completing tasks with a product or prototype. Researchers observe and listen as users express in-the-moment reactions.

Think-aloud testing is ideal when:

• Understanding users’ in-the-moment decision making process and emotional responses is invaluable.
• Insights into points of confusion, frustration, delight can rapidly inform design iterations.
• Users can competently complete tasks while articulating their thinking concurrently.
• Limited time is available compared to extensive ethnographies or diary studies.

Effective think-aloud tips include:

• Provide clear instructions to share thoughts continuously throughout the session. Reassure users.
• Use open-ended prompts like “Tell me what you’re thinking” to encourage articulation without leading.
• Avoid interfering with the user’s process so their commentary feels natural.
• Have users complete realistic, task-based scenarios representative of the product experience.
• Capture direct quotes and time stamp compelling reactions to inform development priorities.

Think-aloud testing efficiently provides a window into users’ in-the-moment perceptions and decision making during hands-on product experiences

Applications Of Qualitative Research

Early product development stages:.

Qualitative user research is invaluable in the early ideation and discovery phases of product development when the problem space is still being explored.

Methods like interviews, ethnographies, and diary studies help researchers deeply understand user needs even before product ideas exist. Qualitative data informs initial user personas, journeys, and use cases so product concepts address real user problems.

Early qualitative insights ensure the end solution resonates with user contexts, attitudes, behaviors and motivations. This upfront user-centricity pays dividends across the entire product lifecycle.

Understanding user needs:

Qualitative techniques directly engage with end users to reveal not just what they do, but why they do it. Immersive interviews unveil users’ unstated needs because researchers can ask follow-up questions on the spot.

Observational studies capture nuanced behaviors that users themselves may not consciously realize or find important to mention. The qualitative emphasis on unlocking the “why” behind user actions is crucial for identifying needs that statistics alone miss. The human-centered discoveries spark innovation opportunities.

Problem identification:

The flexible and exploratory nature of qualitative research allows people to openly share the frustrations, anxieties, and pain points they experience.

Their candid words and emotions convey the meaning behind problems far better than numbers alone. For example, ethnographies and diaries may reveal users’ biggest problems stem not from one specific functionality issue but from misaligned workflows overall.

Qualitative techniques dig into the impacts of problems. The human perspectives guide better solutions.

Understanding context of use:

Well-designed qualitative studies meet users in their natural environments and daily lives. This enables researchers to observe how products and services integrate within existing ecosystems, habits, relationships, and workflows.

Key contextual insights are revealed that surveys alone could miss. For example, home interviews may show a smart speaker’s role in family dynamics. Contextual understanding ensures products fit seamlessly into users’ worlds.

Benefits Of Qualitative Research

Gaining deep insights:.

Qualitative techniques like long-form interviews, think-aloud protocol, and diary studies uncover not just surface-level behaviors and preferences, but the deeper meaning, motivations and emotions behind users’ actions.

Asking probing open-ended questions during in-depth conversations reveals nuanced perspectives on needs, thought processes, pain points, and ecosystems.

Immersive ethnographic observation also provides a holistic view of ingrained user habits and contexts. The richness of these qualitative findings informs truly human-centered innovation opportunities in a way quantitative data alone cannot.

Understanding user emotions:

Qualitative research effectively captures the wide range of emotional aspects of the user experience. Through ethnographic observation, researchers directly see moments of delight during usability testing or frustration while completing a task.

Diary studies provide outlets for users to express perceptions in their own words over time.

In interviews, asking follow-up questions on reactions and feelings provides more color than rating scales. This emotional intelligence helps designers move beyond functional requirements to empathetically address felt needs like enjoyment, trust, accomplishment, and belonging.

Exploring new ideas:

The flexible, conversational nature of qualitative research facilitates creative ideation.

Interactive sessions like focus groups or participatory design workshops allow people to organically share, build on, and iterate on ideas together.

Moderators can probe concepts through clarifying, non-leading questions to draw out nuance and have participants riff on each other’s thoughts. This process efficiently fosters new directions and uncovers latent needs that traditional surveys may never have identified.

Uncovering underlying reasons:

Asking “why” is fundamental to qualitative inquiry. Researchers go beyond documenting surface patterns to uncover the deeper motivations, contextual influences, ingrained habits, and thought processes driving user behaviours.

Observations combined with follow-up interviews provide well-rounded explanations for why people act as they do. For example, apparent routines may be based on social norms versus personal preferences. Qualitative findings explain behavior in a way quantitative data alone often cannot.

Facilitating empathy:

Approaches like ethnography facilitate stepping into the user’s shoes to immerse in their worldview.

Two-way dialogue through long-form interviews allows candid exchange as fellow humans, not detached research subjects. Insights derived from conversations and observations in real-world contexts inspire greater empathy among researchers for users’ needs, frustrations, delights, and realities. Teams feel connected to the people they aim to understand and serve.

Quantitative User Research

Quantitative research seeks to quantify user behaviors, preferences, and attitudes through numerical and statistical analysis. It emphasizes objective measurements and large sample sizes to uncover insights that can be generalized to the broader population.

Key characteristics of quantitative research include:

Structured methodology: 

Quantitative studies utilize highly structured data collection methods like surveys, structured user observation, and user metrics tracking. Surveys rely on closed-ended questions with predefined response options. Observation uses systematic checklists to tally predefined behaviors. This standardization allows mathematical analysis across all participants.

Numerical and statistical analysis: 

The numerical data gathered through quantitative research is analyzed using statistics, aggregates, regressions, and predictive modeling to draw conclusions. Researchers can analyze response frequencies, statistical relationships between variables, segmentation analyses, and predictive models based on the quantitative data.

Large representative samples: 

Quantitative research prioritizes large sample sizes that aim to be representative of the target population. For surveys, sufficient sample sizes are determined using power analyses to ensure findings are generalizable. Some common samples can be in the hundreds to thousands. This is in contrast to smaller qualitative samples aimed at diving deep into individual experiences.

Rating scales: 

Surveys and questionnaires rely heavily on numerical rating scales to quantify subjective attributes like satisfaction, ease-of-use, urgency, importance etc. Respondents rank options or choose numbers that correspond to stances. This assigns discrete values for comparison and statistical testing.

Objectivity : 

Quantitative research focuses on uncovering factual, observable and measurable truths about user behaviors, needs or perceptions. There is less emphasis on gathering subjective viewpoints, contexts, and detailed narratives which are hallmarks of qualitative research. The goal is objective, generalizable insights.

Common Quantitative Research Methods

1. online surveys.

Online surveys involve asking a sample of users to respond to a standardized set of questions delivered through web forms or email. Surveys gather self-reported data on attitudes, preferences, needs and behaviors that can be statistically analyzed.

Online surveys are ideal when:

• A large sample size is needed to gain representative insights from a population.
• Standardized, quantitative data on usages, perceptions, features etc. is desired.
• Users have the literacy level to understand and thoughtfully complete surveys.
• Stakeholders want quantitative metrics, benchmarks and models based on user data.

Effective online survey tips:

• Limit survey length and design clear, focused questions to maintain engagement.
• Structure questions and response options to enable statistical analysis for trends and relationships.
• Use rating scales to quantify subjective attributes like satisfaction, urgency, importance etc.
• Write simple, unambiguous statements users can assess consistently. Avoid leading or loaded language.
• Test surveys before deployment to refine questions and ensure technical functionality.
• Analyze results with statistics and visualizations to glean actionable, user-centered insights.

2. Usability Benchmarking

Usability benchmarking involves assessing a product’s ease-of-use against quantified performance standards and metrics. Researchers conduct structured usability tests to gather performance data that is compared to benchmarks.

Usability benchmarking is ideal when:

• Quantitative goals exist for critical usability metrics like task completion rate, errors, time-on-task, perceived ease-of-use.
• Comparing usability data to other products, previous versions, or industry standards is desired.
• There is a focus on improving usability measured through standardized objectives versus qualitative insights.

Effective usability benchmarking tips:

• Identify key usage tasks and scenarios that align to business goals to standardize testing.
• Leverage established usability metrics like System Usability Scale (SUS) to enable benchmarking.
• Conduct structured tests with representative users on targeted tasks.
• Analyze metrics using statistical methods to surface enhancements tied to benchmarks.
• Set incremental usability goals and continue testing post-launch to drive improvements.

3. Analytics

Analytics involves collecting and analyzing usage data from products to uncover patterns, metrics, and insights about real customer behaviors. Sources like web analytics, app metrics, and usage logs are common.

Analytics excel when:

• Objective data on how customers are actually using a product is needed to optimize features and workflows.
• Large volumes of real customer usage data are available for analysis.
• Revealing segments based on behavioral differences can inform personalized experiences.
• Improving key performance indicators and quantifying impact is a priority.

Effective analytics tips:

• Identify key questions and metrics aligned to business goals to focus analysis. Common metrics are conversions, engagement, retention etc.
• Leverage tools like Google Analytics to collect event and behavioral data at scale.
• Analyze trends, run statistical tests, and build models to surface insights from noise.
• Make insights actionable by tying to opportunities like improving at-risk customer retention.
• Continuously analyze data over time and across updates to optimize ongoing enhancements.

Applications of Quantitative Research

Validating hypotheses:.

Quantitative studies provide statistically robust methods to validate assumptions and confirm hypotheses related to user behaviors or preferences.

After initial qualitative research like interviews raise theories about user needs or pain points, quantitative experiments can verify if those hypotheses hold true at a larger scale.

For example, A/B testing can validate if a new checkout flow improves conversion rates as hypothesized based on earlier usability studies. Statistical validation boosts confidence that recommended changes will have the expected impact on business goals.

Generalizing findings:

The large, representative sample sizes and standardized methodologies in quantitative studies allow findings to be generalized to the full target population with known confidence intervals.

Proper sampling methods ensure data reflects the intended audience demographics, attitudes, and behaviours.

If certain usability benchmarks hold true across hundreds of participants, they are assumed to apply to similar users across that segment. This enables product improvements to be made for broad groups based on generalizable data.

Tracking granular changes:

Quantitative data enables even subtle changes over time, iterative tweaks, or segmented differences to be precisely tracked using consistent metrics.

Longitudinal surveys can pinpoint if customer satisfaction trends upward or downward month-to-month based on new features.

Web analytics continuously monitor click-through rates over years to optimize paths. Controlled A/B tests discern the isolated impact of iterative enhancements. The reliability of quantitative metrics ensures changes are spotted quickly.

Quantifying problem severity:

Statistical analysis in quantitative research can accurately define the frequency and severity of user problems.

For example, an eye-tracking study might uncover 60% of users miss a key navigation element. Surveys can determine what percentage of customers are highly frustrated by unclear documentation.

Quantifying the scope and business impact of issues in this way allows product teams to confidently prioritize the problems with greatest value to solve first.

Benefits of Quantitative Research

Quantifying user behaviours:.

Quantitative methods like analytics, surveys, and usability metrics capture concrete, observable data on how users interact with products.

Usage metrics quantify engagement levels, conversion rates, task completion times, feature adoption, and more. The numerical data enables statistical analysis to uncover trends, model outcomes, and optimize products based on revealed behaviours versus subjective hunches. Quantification also facilitates benchmarking and goal-setting.

Validating hypotheses rigorously:

Quantitative experiments like A/B tests and controlled usability studies allow assumptions and theories about user behaviors to be validated with statistical rigour.

Significant results provide confidence that patterns are real and not due to chance alone. Teams can test hypotheses raised in past qualitative research to prevent high-risk decisions based on false premises. Statistical validation lends credibility to recommended changes expected to impact key metrics.

Precisely tracking granular trends:

The consistent, standardized metrics in quantitative studies powerfully track usage trends over time, across releases, and between user segments. For example, longitudinal surveys can monitor how satisfaction ratings shift month-to-month based on new features.

Web analytics uncover how click-through rates trend up or down over years as needs evolve. Controlled tests isolate the impact of each iteration. Quantitative data spots subtle changes.

Informed decision-making:

Quantitative data provides concrete, measurable evidence of user behaviours, needs, and pain points for informed decision-making.

Metrics on usage, conversions, completion rates, satisfaction, and more enable teams to identify and prioritize issues based on representative data versus hunches. Leaders can justify decisions using statistical significance, projected optimization gains, and benchmark comparisons.

Mitigating biases:

The focus on objective, observable metrics can reduce biases that may inadvertently influence qualitative findings.

Proper sampling methods, significance testing, and controlled experiments also minimize distortions from individual perspectives. While no research is assumption-free, quantitative techniques substantially limit bias through rigorous design and large sample sizes.

Comparing Qualitative and Quantitative User Research

Here is a comparison of qualitative and quantitative user research in a table format:

When to Use Each Method

When to use qualitative research:.

• Early in the product development lifecycle during the fuzzy front-end stages. Open-ended qualitative research is critical for discovering user needs, pain points, and behaviors when the problems are unclear. Qualitative data provides the rich contextual insights required to guide initial solution ideation and design before quantifying anything. Methods like in-depth interviews and contextual inquiries reveal pain points that pure quantitative data often overlooks.
• When research questions are ambiguous, expansive, or nuanced at the start. Qualitative methods can flexibly follow where the data leads to uncover unexpected themes. The fluid approach adapts to capture unforeseen insights, especially on subjective topics like emotions and motivations that require deep probing. Qualitative approaches excel at understanding complex “why” and “how” aspects behind behaviors.
• If seeking highly vivid, detailed narratives of user motivations, ecosystems, thought processes, and needs. Qualitative data maintains all the situational nuance and color intact, not condensed statistically. User stories and perspectives come through with empathy and emotion versus sterile numbers. This level of detail informs truly human-centered solutions.
• During discovery of new market opportunities, expanding into new segments, or exploringnew capabilities with many unknowns. Flexible qualitative digging uncovers fresh territories before attempting to quantify anything. Fuzzy front-end exploration is suited to qualitative exploration.

When to use quantitative research:

• To validate assumptions, theories, and qualitative insights at scale using statistical rigor. Quantitative data provides the confidence that patterns seen are significant and not just anecdotal findings. Surveys, controlled experiments, and metrics test hypotheses raised during qualitative discovery. The statistics offer credibility.
• If research questions aim to precisely quantify target audience behaviors, attitudes, and preferences. Quantitative methods objectively measure “what” users do without room for fuzzy interpretation. The numerical data acts as a precise compass for decision-making.
• When clear metrics and benchmarks are required to set optimization goals, compare design solutions, and tightly track progress. Quantitative data delivers concrete KPIs to orient teams and chart enhancement impact.
• To isolate the precise impact of changes over time or between design solutions by tracking standardized metrics. Controlled A/B tests discern what improvements unequivocally moved key metrics versus speculation.

Frequently Asked Questions (FAQs)

1. What is the main difference between qualitative and quantitative user research?

The main difference is that qualitative research aims to uncover the “why” behind user behaviors through subjective, non-numerical data like interviews and observations. Quantitative research focuses on quantifying the “what” through objective, numerical data like metrics and statistics.

2. Can qualitative and quantitative user research be used together?

Absolutely. Many researchers use a mixed methods approach that combines both qualitative and quantitative techniques to get comprehensive insights. Qualitative research can uncover problems to quantify, while quantitative testing can validate qualitative theories.

3. How do I choose between qualitative and quantitative user research?

Choose based on your current product stage, questions, timeline, and resources. Qualitative research is best for exploratory discovery, while quantitative confirms hypotheses. Use qualitative first, then quantitative or a mix of both.

4. What are some common tools for conducting qualitative and quantitative user research?

Qualitative tools include interviews, focus groups, surveys, user testing and more. Quantitative tools include web analytics, App store metrics, usability metrics, controlled experiments and surveys.

5. What are the limitations of qualitative and quantitative user research?

Qualitative findings are not statistically representative. Quantitative data lacks rich behavioral details. Using both offsets the weaknesses.

• A/B Testing
• Company News
• Conversion Rate Optimisation
• CRO Tools and Resources
• Experimentation Articles
• Google Analytics
• Usability Testing
• User Research
• How To Use Customer Feedback For Website Optimization
• User Research Best Practices for E-commerce Websites
• The Complete Guide to Conducting User Interviews
• 13 AB Testing Best Practices
• How To Write Good Product Descriptions For eCommerce Websites
• The surprising truth about Amazon and Booking.com's culture of experimentation
• Top 19 Best CRO Books (recommended by experts)
• A Complete Guide To User Research
• What Is A CRO Test? Definition, Types & Examples
• User Testing and User Personas: A Synergistic Approach
• Top 8 Free and Paid Mobile App Analytics Tools In 2023
• 3 Usability Testing Methods That Work For UX Insights
• Open-Ended Questions - A Complete Guide
• 5 Ways To Generate CRO Test Ideas That Make A Difference

Is your CRO programme delivering the impact you hoped for ?

Benchmark your CRO now for immediate, free report packed with ACTIONABLE insights you and your team can implement today to increase conversion.

Takes only two minutes

If your CRO programme is not delivering the highest ROI of all of your marketing spend, then we should talk.

Before you go...

“The world’s leading companies are using experimentation to generate better results for the whole business.

Download our latest ebook to discover how businesses have made the shift from CRO to experimentation and how you can too.

Join the next one!

Be the first to know about future events with top speakers from the CRO industry.