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Qualitative vs Quantitative Research Methods & Data Analysis

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

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.

• 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 numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

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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

• Mixed methods research
• 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

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Research methods--quantitative, qualitative, and more: overview.

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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

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START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
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• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

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• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

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• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
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• 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.

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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 .

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Raimo Streefkerk

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!

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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

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Qualitative Research: Getting Started

Zubin austin, jane sutton.

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Address correspondence to: Dr Zubin Austin, Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto ON M5S 3M2, e-mail: [email protected]

INTRODUCTION

As scientifically trained clinicians, pharmacists may be more familiar and comfortable with the concept of quantitative rather than qualitative research. Quantitative research can be defined as “the means for testing objective theories by examining the relationship among variables which in turn can be measured so that numbered data can be analyzed using statistical procedures”. 1 Pharmacists may have used such methods to carry out audits or surveys within their own practice settings; if so, they may have had a sense of “something missing” from their data. What is missing from quantitative research methods is the voice of the participant. In a quantitative study, large amounts of data can be collected about the number of people who hold certain attitudes toward their health and health care, but what qualitative study tells us is why people have thoughts and feelings that might affect the way they respond to that care and how it is given (in this way, qualitative and quantitative data are frequently complementary). Possibly the most important point about qualitative research is that its practitioners do not seek to generalize their findings to a wider population. Rather, they attempt to find examples of behaviour, to clarify the thoughts and feelings of study participants, and to interpret participants’ experiences of the phenomena of interest, in order to find explanations for human behaviour in a given context.

WHAT IS QUALITATIVE RESEARCH?

Much of the work of clinicians (including pharmacists) takes place within a social, clinical, or interpersonal context where statistical procedures and numeric data may be insufficient to capture how patients and health care professionals feel about patients’ care. Qualitative research involves asking participants about their experiences of things that happen in their lives. It enables researchers to obtain insights into what it feels like to be another person and to understand the world as another experiences it.

Qualitative research was historically employed in fields such as sociology, history, and anthropology. 2 Miles and Huberman 2 said that qualitative data “are a source of well-grounded, rich descriptions and explanations of processes in identifiable local contexts. With qualitative data one can preserve chronological flow, see precisely which events lead to which consequences, and derive fruitful explanations.” Qualitative methods are concerned with how human behaviour can be explained, within the framework of the social structures in which that behaviour takes place. 3 So, in the context of health care, and hospital pharmacy in particular, researchers can, for example, explore how patients feel about their care, about their medicines, or indeed about “being a patient”.

THE IMPORTANCE OF METHODOLOGY

Smith 4 has described methodology as the “explanation of the approach, methods and procedures with some justification for their selection.” It is essential that researchers have robust theories that underpin the way they conduct their research—this is called “methodology”. It is also important for researchers to have a thorough understanding of various methodologies, to ensure alignment between their own positionality (i.e., bias or stance), research questions, and objectives. Clinicians may express reservations about the value or impact of qualitative research, given their perceptions that it is inherently subjective or biased, that it does not seek to be reproducible across different contexts, and that it does not produce generalizable findings. Other clinicians may express nervousness or hesitation about using qualitative methods, claiming that their previous “scientific” training and experience have not prepared them for the ambiguity and interpretative nature of qualitative data analysis. In both cases, these clinicians are depriving themselves of opportunities to understand complex or ambiguous situations, phenomena, or processes in a different way.

Qualitative researchers generally begin their work by recognizing that the position (or world view) of the researcher exerts an enormous influence on the entire research enterprise. Whether explicitly understood and acknowledged or not, this world view shapes the way in which research questions are raised and framed, methods selected, data collected and analyzed, and results reported. 5 A broad range of different methods and methodologies are available within the qualitative tradition, and no single review paper can adequately capture the depth and nuance of these diverse options. Here, given space constraints, we highlight certain options for illustrative purposes only, emphasizing that they are only a sample of what may be available to you as a prospective qualitative researcher. We encourage you to continue your own study of this area to identify methods and methodologies suitable to your questions and needs, beyond those highlighted here.

The following are some of the methodologies commonly used in qualitative research:

Ethnography generally involves researchers directly observing participants in their natural environments over time. A key feature of ethnography is the fact that natural settings, unadapted for the researchers’ interests, are used. In ethnography, the natural setting or environment is as important as the participants, and such methods have the advantage of explicitly acknowledging that, in the real world, environmental constraints and context influence behaviours and outcomes. 6 An example of ethnographic research in pharmacy might involve observations to determine how pharmacists integrate into family health teams. Such a study would also include collection of documents about participants’ lives from the participants themselves and field notes from the researcher. 7

Grounded theory, first described by Glaser and Strauss in 1967, 8 is a framework for qualitative research that suggests that theory must derive from data, unlike other forms of research, which suggest that data should be used to test theory. Grounded theory may be particularly valuable when little or nothing is known or understood about a problem, situation, or context, and any attempt to start with a hypothesis or theory would be conjecture at best. 9 An example of the use of grounded theory in hospital pharmacy might be to determine potential roles for pharmacists in a new or underserviced clinical area. As with other qualitative methodologies, grounded theory provides researchers with a process that can be followed to facilitate the conduct of such research. As an example, Thurston and others 10 used constructivist grounded theory to explore the availability of arthritis care among indigenous people of Canada and were able to identify a number of influences on health care for this population.

Phenomenology attempts to understand problems, ideas, and situations from the perspective of common understanding and experience rather than differences. 10 Phenomenology is about understanding how human beings experience their world. It gives researchers a powerful tool with which to understand subjective experience. In other words, 2 people may have the same diagnosis, with the same treatment prescribed, but the ways in which they experience that diagnosis and treatment will be different, even though they may have some experiences in common. Phenomenology helps researchers to explore those experiences, thoughts, and feelings and helps to elicit the meaning underlying how people behave. As an example, Hancock and others 11 used a phenomenological approach to explore health care professionals’ views of the diagnosis and management of heart failure since publication of an earlier study in 2003. Their findings revealed that barriers to effective treatment for heart failure had not changed in 10 years and provided a new understanding of why this was the case.

ROLE OF THE RESEARCHER

For any researcher, the starting point for research must be articulation of his or her research world view. This core feature of qualitative work is increasingly seen in quantitative research too: the explicit acknowledgement of one’s position, biases, and assumptions, so that readers can better understand the particular researcher. Reflexivity describes the processes whereby the act of engaging in research actually affects the process being studied, calling into question the notion of “detached objectivity”. Here, the researcher’s own subjectivity is as critical to the research process and output as any other variable. Applications of reflexivity may include participant-observer research, where the researcher is actually one of the participants in the process or situation being researched and must then examine it from these divergent perspectives. 12 Some researchers believe that objectivity is a myth and that attempts at impartiality will fail because human beings who happen to be researchers cannot isolate their own backgrounds and interests from the conduct of a study. 5 Rather than aspire to an unachievable goal of “objectivity”, it is better to simply be honest and transparent about one’s own subjectivities, allowing readers to draw their own conclusions about the interpretations that are presented through the research itself. For new (and experienced) qualitative researchers, an important first step is to step back and articulate your own underlying biases and assumptions. The following questions can help to begin this reflection process:

Why am I interested in this topic? To answer this question, try to identify what is driving your enthusiasm, energy, and interest in researching this subject.

What do I really think the answer is? Asking this question helps to identify any biases you may have through honest reflection on what you expect to find. You can then “bracket” those assumptions to enable the participants’ voices to be heard.

What am I getting out of this? In many cases, pressures to publish or “do” research make research nothing more than an employment requirement. How does this affect your interest in the question or its outcomes, or the depth to which you are willing to go to find information?

What do others in my professional community think of this work—and of me? As a researcher, you will not be operating in a vacuum; you will be part of a complex social and interpersonal world. These external influences will shape your views and expectations of yourself and your work. Acknowledging this influence and its potential effects on personal behaviour will facilitate greater self-scrutiny throughout the research process.

FROM FRAMEWORKS TO METHODS

Qualitative research methodology is not a single method, but instead offers a variety of different choices to researchers, according to specific parameters of topic, research question, participants, and settings. The method is the way you carry out your research within the paradigm of quantitative or qualitative research.

Qualitative research is concerned with participants’ own experiences of a life event, and the aim is to interpret what participants have said in order to explain why they have said it. Thus, methods should be chosen that enable participants to express themselves openly and without constraint. The framework selected by the researcher to conduct the research may direct the project toward specific methods. From among the numerous methods used by qualitative researchers, we outline below the three most frequently encountered.

DATA COLLECTION

Patton 12 has described an interview as “open-ended questions and probes yielding in-depth responses about people’s experiences, perceptions, opinions, feelings, and knowledge. Data consists of verbatim quotations and sufficient content/context to be interpretable”. Researchers may use a structured or unstructured interview approach. Structured interviews rely upon a predetermined list of questions framed algorithmically to guide the interviewer. This approach resists improvisation and following up on hunches, but has the advantage of facilitating consistency between participants. In contrast, unstructured or semistructured interviews may begin with some defined questions, but the interviewer has considerable latitude to adapt questions to the specific direction of responses, in an effort to allow for more intuitive and natural conversations between researchers and participants. Generally, you should continue to interview additional participants until you have saturated your field of interest, i.e., until you are not hearing anything new. The number of participants is therefore dependent on the richness of the data, though Miles and Huberman 2 suggested that more than 15 cases can make analysis complicated and “unwieldy”.

Focus Groups

Patton 12 has described the focus group as a primary means of collecting qualitative data. In essence, focus groups are unstructured interviews with multiple participants, which allow participants and a facilitator to interact freely with one another and to build on ideas and conversation. This method allows for the collection of group-generated data, which can be a challenging experience.

Observations

Patton 12 described observation as a useful tool in both quantitative and qualitative research: “[it involves] descriptions of activities, behaviours, actions, conversations, interpersonal interactions, organization or community processes or any other aspect of observable human experience”. Observation is critical in both interviews and focus groups, as nonalignment between verbal and nonverbal data frequently can be the result of sarcasm, irony, or other conversational techniques that may be confusing or open to interpretation. Observation can also be used as a stand-alone tool for exploring participants’ experiences, whether or not the researcher is a participant in the process.

Selecting the most appropriate and practical method is an important decision and must be taken carefully. Those unfamiliar with qualitative research may assume that “anyone” can interview, observe, or facilitate a focus group; however, it is important to recognize that the quality of data collected through qualitative methods is a direct reflection of the skills and competencies of the researcher. 13 The hardest thing to do during an interview is to sit back and listen to participants. They should be doing most of the talking—it is their perception of their own life-world that the researcher is trying to understand. Sophisticated interpersonal skills are required, in particular the ability to accurately interpret and respond to the nuanced behaviour of participants in various settings. More information about the collection of qualitative data may be found in the “Further Reading” section of this paper.

It is essential that data gathered during interviews, focus groups, and observation sessions are stored in a retrievable format. The most accurate way to do this is by audio-recording (with the participants’ permission). Video-recording may be a useful tool for focus groups, because the body language of group members and how they interact can be missed with audio-recording alone. Recordings should be transcribed verbatim and checked for accuracy against the audio- or video-recording, and all personally identifiable information should be removed from the transcript. You are then ready to start your analysis.

DATA ANALYSIS

Regardless of the research method used, the researcher must try to analyze or make sense of the participants’ narratives. This analysis can be done by coding sections of text, by writing down your thoughts in the margins of transcripts, or by making separate notes about the data collection. Coding is the process by which raw data (e.g., transcripts from interviews and focus groups or field notes from observations) are gradually converted into usable data through the identification of themes, concepts, or ideas that have some connection with each other. It may be that certain words or phrases are used by different participants, and these can be drawn together to allow the researcher an opportunity to focus findings in a more meaningful manner. The researcher will then give the words, phrases, or pieces of text meaningful names that exemplify what the participants are saying. This process is referred to as “theming”. Generating themes in an orderly fashion out of the chaos of transcripts or field notes can be a daunting task, particularly since it may involve many pages of raw data. Fortunately, sophisticated software programs such as NVivo (QSR International Pty Ltd) now exist to support researchers in converting data into themes; familiarization with such software supports is of considerable benefit to researchers and is strongly recommended. Manual coding is possible with small and straightforward data sets, but the management of qualitative data is a complexity unto itself, one that is best addressed through technological and software support.

There is both an art and a science to coding, and the second checking of themes from data is well advised (where feasible) to enhance the face validity of the work and to demonstrate reliability. Further reliability-enhancing mechanisms include “member checking”, where participants are given an opportunity to actually learn about and respond to the researchers’ preliminary analysis and coding of data. Careful documentation of various iterations of “coding trees” is important. These structures allow readers to understand how and why raw data were converted into a theme and what rules the researcher is using to govern inclusion or exclusion of specific data within or from a theme. Coding trees may be produced iteratively: after each interview, the researcher may immediately code and categorize data into themes to facilitate subsequent interviews and allow for probing with subsequent participants as necessary. At the end of the theming process, you will be in a position to tell the participants’ stories illustrated by quotations from your transcripts. For more information on different ways to manage qualitative data, see the “Further Reading” section at the end of this paper.

ETHICAL ISSUES

In most circumstances, qualitative research involves human beings or the things that human beings produce (documents, notes, etc.). As a result, it is essential that such research be undertaken in a manner that places the safety, security, and needs of participants at the forefront. Although interviews, focus groups, and questionnaires may seem innocuous and “less dangerous” than taking blood samples, it is important to recognize that the way participants are represented in research can be significantly damaging. Try to put yourself in the shoes of the potential participants when designing your research and ask yourself these questions:

Are the requests you are making of potential participants reasonable?

Are you putting them at unnecessary risk or inconvenience?

Have you identified and addressed the specific needs of particular groups?

Where possible, attempting anonymization of data is strongly recommended, bearing in mind that true anonymization may be difficult, as participants can sometimes be recognized from their stories. Balancing the responsibility to report findings accurately and honestly with the potential harm to the participants involved can be challenging. Advice on the ethical considerations of research is generally available from research ethics boards and should be actively sought in these challenging situations.

GETTING STARTED

Pharmacists may be hesitant to embark on research involving qualitative methods because of a perceived lack of skills or confidence. Overcoming this barrier is the most important first step, as pharmacists can benefit from inclusion of qualitative methods in their research repertoire. Partnering with others who are more experienced and who can provide mentorship can be a valuable strategy. Reading reports of research studies that have utilized qualitative methods can provide insights and ideas for personal use; such papers are routinely included in traditional databases accessed by pharmacists. Engaging in dialogue with members of a research ethics board who have qualitative expertise can also provide useful assistance, as well as saving time during the ethics review process itself. The references at the end of this paper may provide some additional support to allow you to begin incorporating qualitative methods into your research.

CONCLUSIONS

Qualitative research offers unique opportunities for understanding complex, nuanced situations where interpersonal ambiguity and multiple interpretations exist. Qualitative research may not provide definitive answers to such complex questions, but it can yield a better understanding and a springboard for further focused work. There are multiple frameworks, methods, and considerations involved in shaping effective qualitative research. In most cases, these begin with self-reflection and articulation of positionality by the researcher. For some, qualitative research may appear commonsensical and easy; for others, it may appear daunting, given its high reliance on direct participant– researcher interactions. For yet others, qualitative research may appear subjective, unscientific, and consequently unreliable. All these perspectives reflect a lack of understanding of how effective qualitative research actually occurs. When undertaken in a rigorous manner, qualitative research provides unique opportunities for expanding our understanding of the social and clinical world that we inhabit.

Further Reading

• Breakwell GM, Hammond S, Fife-Schaw C, editors. Research methods in psychology. Thousand Oaks (CA): Sage Publications Ltd; 1995. [ Google Scholar ]
• Strauss A, Corbin J. Basics of qualitative research. Thousand Oaks (CA): Sage Publications Ltd; 1998. [ Google Scholar ]
• Willig C. Introducing qualitative research in psychology. Buckingham (UK): Open University Press; 2001. [ Google Scholar ]
• Guest G, Namey EE, Mitchel ML. Collecting qualitative data: a field manual for applied research. Thousand Oaks (CA): Sage Publications Ltd; 2013. [ Google Scholar ]
• Ogden R. Bias. In: Given LM, editor. The Sage encyclopedia of qualitative research methods. Thousand Oaks (CA): Sage Publications Inc; 2008. pp. 61–2. [ Google Scholar ]

This article is the seventh in the CJHP Research Primer Series, an initiative of the CJHP Editorial Board and the CSHP Research Committee. The planned 2-year series is intended to appeal to relatively inexperienced researchers, with the goal of building research capacity among practising pharmacists. The articles, presenting simple but rigorous guidance to encourage and support novice researchers, are being solicited from authors with appropriate expertise.

Previous article in this series:

Bond CM. The research jigsaw: how to get started. Can J Hosp Pharm . 2014;67(1):28–30.

Tully MP. Research: articulating questions, generating hypotheses, and choosing study designs. Can J Hosp Pharm . 2014;67(1):31–4.

Loewen P. Ethical issues in pharmacy practice research: an introductory guide. Can J Hosp Pharm. 2014;67(2):133–7.

Tsuyuki RT. Designing pharmacy practice research trials. Can J Hosp Pharm . 2014;67(3):226–9.

Bresee LC. An introduction to developing surveys for pharmacy practice research. Can J Hosp Pharm . 2014;67(4):286–91.

Gamble JM. An introduction to the fundamentals of cohort and case–control studies. Can J Hosp Pharm . 2014;67(5):366–72.

Competing interests: None declared.

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15 Types of Research Methods

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

• Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
• Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

• Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
• Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

• Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
• Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Example of Ethnography

Liquidated: An Ethnography of Wall Street  by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Example of Phenomenological Research

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Example of Content Analysis

How is Islam Portrayed in Western Media?  by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory  during and after  data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Grounded Theory Example

Developing a Leadership Identity   by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing   by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or  negative correlation trends  that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

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What Is Qualitative vs. Quantitative Study?

Qualitative research focuses on understanding phenomena through detailed, narrative data. It explores the “how” and “why” of human behavior, using methods like interviews, observations, and content analysis. In contrast, quantitative research is numeric and objective, aiming to quantify variables and analyze statistical relationships. It addresses the “when” and “where,” utilizing tools like surveys, experiments, and statistical models to collect and analyze numerical data.

In This Article:

What is qualitative research, what is quantitative research.

• How Do Qualitative and Quantitative Research Differ?

What’s the Difference Between a Qualitative and Quantitative Study?

Analyzing qualitative and quantitative data, when to use qualitative or quantitative research, develop your research skills at national university.

Qualitative and quantitative data are broad categories covering many research approaches and methods. While both share the primary aim of knowledge acquisition, quantitative research is numeric and objective, seeking to answer questions like when or where. On the other hand, qualitative research is concerned with subjective phenomena that can’t be numerically measured, like how different people experience grief.

Having a firm grounding in qualitative and quantitative research methodologies will become especially important once you begin work on your dissertation or thesis toward the end of your academic program. At that point, you’ll need to decide which approach best aligns with your research question, a process that involves working closely with your Dissertation Chair.

Keep reading to learn more about the difference between quantitative vs. qualitative research, including what research techniques they involve, how they approach the task of data analysis, and some strengths — and limitations — of each approach. We’ll also briefly examine mixed-method research, which incorporates elements of both methodologies.

Qualitative research differs from quantitative research in its objectives, techniques, and design. Qualitative research aims to gain insights into phenomena, groups, or experiences that cannot be objectively measured or quantified using mathematics. Instead of seeking to uncover precise answers or statistics in a controlled environment like quantitative research, qualitative research is more exploratory, drawing upon data sources such as photographs, journal entries, video footage, and interviews.

These features stand in stark contrast to quantitative research, as we’ll see throughout the remainder of this article.

Quantitative research tackles questions from different angles compared to qualitative research. Instead of probing for subjective meaning by asking exploratory “how?” and “why?” questions, quantitative research provides precise causal explanations that can be measured and communicated mathematically. While qualitative researchers might visit subjects in their homes or otherwise in the field, quantitative research is usually conducted in a controlled environment. Instead of gaining insight or understanding into a subjective, context-dependent issue, as is the case with qualitative research, the goal is instead to obtain objective information, such as determining the best time to undergo a specific medical procedure.

How Does Qualitative and Quantitative Research Differ?

How are the approaches of quantitative and qualitative research different?

In qualitative studies, data is usually gathered in the field from smaller sample sizes, which means researchers might personally visit participants in their own homes or other environments. Once the research is completed, the researcher must evaluate and make sense of the data in its context, looking for trends or patterns from which new theories, concepts, narratives, or hypotheses can be generated.

Quantitative research is typically carried out via tools (such as questionnaires) instead of by people (such as a researcher asking interview questions). Another significant difference is that, in qualitative studies, researchers must interpret the data to build hypotheses. In a quantitative analysis, the researcher sets out to test a hypothesis.

Both qualitative and quantitative studies are subject to rigorous quality standards. However, the research techniques utilized in each type of study differ, as do the questions and issues they hope to address or resolve. In quantitative studies, researchers tend to follow more rigid structures to test the links or relationships between different variables, ideally based on a random sample. On the other hand, in a qualitative study, not only are the samples typically smaller and narrower (such as using convenience samples), the study’s design is generally more flexible and less structured to accommodate the open-ended nature of the research.

Below are a few examples of qualitative and quantitative research techniques to help illustrate these differences further.

Sources of Quantitative Research

Some example methods of quantitative research methods or sources include, but are not limited to, the following:

• Conducting polls, surveys, and experiments
• Compiling databases of records and information
• Observing the topic of the research, such as a specific reaction
• Performing a meta-analysis, which involves analyzing multiple prior studies in order to identify statistical trends or patterns
• Supplying online or paper questionnaires to participants

The following section will cover some examples of qualitative research methods for comparison, followed by an overview of mixed research methods that blend components of both approaches.

Sources of Qualitative Research

Researchers can use numerous qualitative methods to explore a topic or gain insight into an issue. Some sources of, or approaches to, qualitative research include the following examples:

• Conducting ethnographic studies, which are studies that seek to explore different phenomena through a cultural or group-specific lens
• Conducting focus groups
• Examining various types of records, including but not limited to diary entries, personal letters, official documents, medical or hospital records, photographs, video or audio recordings, and even minutes from meetings
• Holding one-on-one interviews
• Obtaining personal accounts and recollections of events or experiences

Examples of Research Questions Best Suited for Qualitative vs. Quantitative Methods

Qualitative research questions:.

• How do patients experience the process of recovering from surgery?
• Why do some employees feel more motivated in remote work environments?
• What are the cultural influences on dietary habits among teenagers?

Quantitative Research Questions:

• What is the average recovery time for patients after surgery?
• How does remote work impact employee productivity levels?
• What percentage of teenagers adhere to recommended dietary guidelines?

These examples illustrate how qualitative research delves into the depth and context of human experiences, while quantitative research focuses on measurable data and statistical analysis.

Mixed Methods Research

In addition to the purely qualitative and quantitative research methods outlined above, such as conducting focus groups or performing meta-analyses, it’s also possible to take a hybrid approach that merges qualitative and quantitative research aspects. According to an article published by LinkedIn , “Mixed methods research avoids many [of the] criticisms” that have historically been directed at qualitative and quantitative research, such as the former’s vulnerability to bias, by “canceling the effects of one methodology by including the other methodology.” In other words, this mixed approach provides the best of both worlds. “Mixed methods research also triangulates results that offer higher validity and reliability.”

If you’re enrolled as a National University student, you can watch a video introduction to mixed-method research by logging in with your student ID. Our resource library also covers qualitative and quantitative research methodologies and a video breakdown of when to use which approach.

When it comes to quantitative and qualitative research, methods of collecting data differ, as do the methods of organizing and analyzing it. So what are some best practices for analyzing qualitative and quantitative data sets, and how do they call for different approaches by researchers?

How to Analyze Qualitative Data

Below is a step-by-step overview of how to analyze qualitative data.

• Make sure all of your data is finished being compiled before you begin any analysis.
• Organize and connect your data for consistency using computer-assisted qualitative data analysis software (CAQDAS).
• Code your data, which can be partially automated using a feedback analytics platform.
• Start digging deep into analysis, potentially using augmented intelligence to get more accurate results.
• Report on your findings, ideally using engaging aids to help tell the story.

How to Analyze Quantitative Data

There are numerous approaches to analyzing quantitative data. Some examples include cross-tabulation, conjoint analysis, gap analysis, trend analysis, and SWOT analysis, which refers to Strengths, Weaknesses, Opportunities, and Threats.

Whichever system or systems you use, there are specific steps you should take to ensure that you’ve organized your data and analyzed it as accurately as possible. Here’s a brief four-step overview.

• Connect measurement scales to study variables, which helps ensure that your data will be organized in the appropriate order before you proceed.
• Link data with descriptive statistics, such as mean, median, mode, or frequency.
• Determine what measurement scale you’ll use for your analysis.
• Organize the data into tables and conduct an analysis using methods like cross-tabulation or Total Unduplicated Reach and Frequency (TURF) analysis.

Simply knowing the difference between quantitative and qualitative research isn’t enough — you also need an understanding of when each approach should be used and under what circumstances. For that, you’ll need to consider all of the comparisons we’ve made throughout this article and weigh some potential pros and cons of each methodology.

Pros and Cons of Qualitative Research

Qualitative research has numerous strengths, but the research methodology is only more appropriate for some projects or dissertations. Here are some strengths and weaknesses of qualitative research to help guide your decision:

• Pro — More flex room for creativity and interpretation of results
• Pro — Greater freedom to utilize different research techniques as the study evolves
• Con — Potentially more vulnerable to bias due to their subjective nature
• Con — Sample sizes tend to be smaller and non-randomized

Pros and Cons of Quantitative Research

Quantitative research also comes with drawbacks and benefits, depending on what information you aim to uncover. Here are a few pros and cons to consider when designing your study.

• Pro — Large, random samples help ensure that the broader population is more realistically reflected
• Pro — Specific, precise results can be easily communicated using numbers
• Con — Data can suffer from a lack of context or personal detail around participant answers
• Con — Numerous participants are needed, driving up costs while posing logistical challenges

If you dream of making a scientific breakthrough and contributing new knowledge that revolutionizes your field, you’ll need a strong foundation in research, from how it’s conducted and analyzed to a clear understanding of professional ethics and standards. By pursuing your degree at National University, you build stronger research skills and countless other in-demand job skills.

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The differences between qualitative and quantitative research methods

Last updated

15 January 2023

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Two approaches to this systematic information gathering are qualitative and quantitative research. Each of these has its place in data collection, but each one approaches from a different direction. Here's what you need to know about qualitative and quantitative research.

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• The differences between quantitative and qualitative research

The main difference between these two approaches is the type of data you collect and how you interpret it. Qualitative research focuses on word-based data, aiming to define and understand ideas. This study allows researchers to collect information in an open-ended way through interviews, ethnography, and observation. You’ll study this information to determine patterns and the interplay of variables.

On the other hand, quantitative research focuses on numerical data and using it to determine relationships between variables. Researchers use easily quantifiable forms of data collection, such as experiments that measure the effect of one or several variables on one another.

• Qualitative vs. quantitative data collection

Focusing on different types of data means that the data collection methods vary. 

Quantitative data collection methods

As previously stated, quantitative data collection focuses on numbers. You gather information through experiments, database reports, or surveys with multiple-choice answers. The goal is to have data you can use in numerical analysis to determine relationships.

Qualitative data collection methods

On the other hand, the data collected for qualitative research is an exploration of a subject's attributes, thoughts, actions, or viewpoints. Researchers will typically conduct interviews , hold focus groups, or observe behavior in a natural setting to assemble this information. Other options include studying personal accounts or cultural records. 

• Qualitative vs. quantitative outcomes

The two approaches naturally produce different types of outcomes. Qualitative research gains a better understanding of the reason something happens. For example, researchers may comb through feedback and statements to ascertain the reasoning behind certain behaviors or actions.

On the other hand, quantitative research focuses on the numerical analysis of data, which may show cause-and-effect relationships. Put another way, qualitative research investigates why something happens, while quantitative research looks at what happens.

• How to analyze qualitative and quantitative data

Because the two research methods focus on different types of information, analyzing the data you've collected will look different, depending on your approach.

Analyzing quantitative data

As this data is often numerical, you’ll likely use statistical analysis to identify patterns. Researchers may use computer programs to generate data such as averages or rate changes, illustrating the results in tables or graphs.

Analyzing qualitative data

Qualitative data is more complex and time-consuming to process as it may include written texts, videos, or images to study. Finding patterns in thinking, actions, and beliefs is more nuanced and subject to interpretation. 

Researchers may use techniques such as thematic analysis , combing through the data to identify core themes or patterns. Another tool is discourse analysis , which studies how communication functions in different contexts.

• When to use qualitative vs. quantitative research

Choosing between the two approaches comes down to understanding what your goal is with the research.

Qualitative research approach

Qualitative research is useful for understanding a concept, such as what people think about certain experiences or how cultural beliefs affect perceptions of events. It can help you formulate a hypothesis or clarify general questions about the topic.

Quantitative research approach

On the other hand, quantitative research verifies or tests a hypothesis you've developed, or you can use it to find answers to those questions. 

Mixed methods approach

Often, researchers use elements of both types of research to provide complex and targeted information. This may look like a survey with multiple-choice and open-ended questions.

• Benefits and limitations

Of course, each type of research has drawbacks and strengths. It's essential to be aware of the pros and cons.

Qualitative studies: Pros and cons

This approach lets you consider your subject creatively and examine big-picture questions. It can advance your global understanding of topics that are challenging to quantify.

On the other hand, the wide-open possibilities of qualitative research can make it tricky to focus effectively on your subject of inquiry. It makes it easier for researchers to skew the data with social biases and personal assumptions. There’s also the tendency for people to behave differently under observation.

It can also be more difficult to get a large sample size because it's generally more complex and expensive to conduct qualitative research. The process usually takes longer, as well. 

Quantitative studies: Pros and cons

The quantitative methodology produces data you can communicate and present without bias. The methods are direct and generally easier to reproduce on a larger scale, enabling researchers to get accurate results. It can be instrumental in pinning down precise facts about a topic. 

It is also a restrictive form of inquiry. Researchers cannot add context to this type of data collection or expand their focus in a different direction within a single study. They must be alert for biases. Quantitative research is more susceptible to selection bias and omitting or incorrectly measuring variables.

• How to balance qualitative and quantitative research

Although people tend to gravitate to one form of inquiry over another, each has its place in studying a subject. Both approaches can identify patterns illustrating the connection between multiple elements, and they can each advance your understanding of subjects in important ways. 

Understanding how each option will serve you will help you decide how and when to use each. Generally, qualitative research can help you develop and refine questions, while quantitative research helps you get targeted answers to those questions. Which element do you need to advance your study of the subject? Can both of them hone your knowledge?

Open-ended vs. close-ended questions

One way to use techniques from both approaches is with open-ended and close-ended questions in surveys. Because quantitative analysis requires defined sets of data that you can represent numerically, the questions must be close-ended. On the other hand, qualitative inquiry is naturally open-ended, allowing room for complex ideas.

An example of this is a survey on the impact of inflation. You could include both multiple-choice questions and open-response questions:

1. How do you compensate for higher prices at the grocery store? (Select all that apply)

A. Purchase fewer items

B. Opt for less expensive choices

C. Take money from other parts of the budget

D. Use a food bank or other charity to fill the gaps

E. Make more food from scratch

2. How do rising prices affect your grocery shopping habits? (Write your answer)

We need qualitative and quantitative forms of research to advance our understanding of the world. Neither is the "right" way to go, but one may be better for you depending on your needs. 

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Qualitative and Quantitative Research

In general, quantitative research seeks to understand the causal or correlational relationship between variables through testing hypotheses, whereas qualitative research seeks to understand a phenomenon within a real-world context through the use of interviews and observation. Both types of research are valid, and certain research topics are better suited to one approach or the other. However, it is important to understand the differences between qualitative and quantitative research so that you will be able to conduct an informed critique and analysis of any articles that you read, because you will understand the different advantages, disadvantages, and influencing factors for each approach. 

The table below illustrates the main differences between qualitative and quantitative research. Be aware that these are generalizations, and that not every research study or article will fit neatly into these categories. 

Systematic reviews, meta-analyses, and integrative reviews are not exactly designs, but they synthesize, analyze, and compare the results from many research studies and are somewhat quantitative in nature. However, they are not truly quantitative or qualitative studies.

References:

LoBiondo-Wood, G., & Haber, J. (2010). Nursing research: Methods and critical appraisal for evidence-based practice (7 th ed.). St. Louis, MO: Mosby Elsevier

Mertens, D. M. (2010). Research and evaluation in education and psychology (3 rd ed.). Los Angeles: SAGE

Quick Overview

This 2-minute video provides a simplified overview of the primary distinctions between quantitative and qualitative research.

It's Not Always One or the Other!

It's important to keep in mind that research studies and articles are not always 100% qualitative or 100% quantitative. A mixed methods study involves both qualitative and quantitative approaches. If you need to find articles that are purely qualitative or purely quanititative, be sure to look carefully at the methodology sections to make sure the studies did not utilize both methods. 

• Next: Nursing >>
• Last Updated: May 28, 2024 4:52 PM
• URL: https://stevenson.libguides.com/c.php?g=236343

Quantitative vs. Qualitative Research Design: Understanding the Differences

As a future professional in the social and education landscape, research design is one of the most critical strategies that you will master to identify challenges, ask questions and form data-driven solutions to address problems specific to your industry. 

Many approaches to research design exist, and not all work in every circumstance. While all data-focused research methods are valid in their own right, certain research design methods are more appropriate for specific study objectives.

Unlock our resource to learn more about jump starting a career in research design — Research Design and Data Analysis for the Social Good .

We will discuss the differences between quantitative (numerical and statistics-focused) and qualitative (non-numerical and human-focused) research design methods so that you can determine which approach is most strategic given your specific area of graduate-level study. 

Understanding Social Phenomena: Qualitative Research Design

Qualitative research focuses on understanding a phenomenon based on human experience and individual perception. It is a non-numerical methodology relying on interpreting a process or result. Qualitative research also paves the way for uncovering other hypotheses related to social phenomena. 

In its most basic form, qualitative research is exploratory in nature and seeks to understand the subjective experience of individuals based on social reality.

Qualitative data is…

• often used in fields related to education, sociology and anthropology; 
• designed to arrive at conclusions regarding social phenomena; 
• focused on data-gathering techniques like interviews, focus groups or case studies; 
• dedicated to perpetuating a flexible, adaptive approach to data gathering;
• known to lead professionals to deeper insights within the overall research study.

You want to use qualitative data research design if:

• you work in a field concerned with enhancing humankind through the lens of social change;
• your research focuses on understanding complex social trends and individual perceptions of those trends;
• you have interests related to human development and interpersonal relationships.

Examples of Qualitative Research Design in Education

Here are just a few examples of how qualitative research design methods can impact education:

Example 1: Former educators participate in in-depth interviews to help determine why a specific school is experiencing a higher-than-average turnover rate compared to other schools in the region. These interviews help determine the types of resources that will make a difference in teacher retention. 

Example 2: Focus group discussions occur to understand the challenges that neurodivergent students experience in the classroom daily. These discussions prepare administrators, staff, teachers and parents to understand the kinds of support that will augment and improve student outcomes.

Example 3: Case studies examine the impacts of a new education policy that limits the number of teacher aids required in a special needs classroom. These findings help policymakers determine whether the new policy affects the learning outcomes of a particular class of students.

Interpreting the Numbers: Quantitative Research Design

Quantitative research tests hypotheses and measures connections between variables. It relies on insights derived from numbers — countable, measurable and statistically sound data. Quantitative research is a strategic research design used when basing critical decisions on statistical conclusions and quantifiable data.

Quantitative research provides numerical-backed quantifiable data that may approve or discount a theory or hypothesis.

Quantitative data is…

• often used in fields related to education, data analysis and healthcare; 
• designed to arrive at numerical, statistical conclusions based on objective facts;
• focused on data-gathering techniques like experiments, surveys or observations;
• dedicated to using mathematical principles to arrive at conclusions;
• known to lead professionals to indisputable observations within the overall research study.

You want to use quantitative data research design if:

• you work in a field concerned with analyzing data to inform decisions;
• your research focuses on studying relationships between variables to form data-driven conclusions;
• you have interests related to mathematics, statistical analysis and data science.

Examples of Quantitative Research Design in Education

Here are just a few examples of how quantitative research design methods may impact education:

Example 1: Researchers compile data to understand the connection between class sizes and standardized test scores. Researchers can determine if and what the relationship is between smaller, intimate class sizes and higher test scores for grade-school children using statistical and data analysis.

Example 2: Professionals conduct an experiment in which a group of high school students must complete a certain number of community service hours before graduation. Researchers compare those students to another group of students who did not complete service hours — using statistical analysis to determine if the requirement increased college acceptance rates.

Example 3: Teachers take a survey to examine an education policy that restricts the number of extracurricular activities offered at a particular academic institution. The findings help better understand the far-reaching impacts of extracurricular opportunities on academic performance.

Making the Most of Research Design Methods for Good: Vanderbilt University’s Peabody College

Vanderbilt University's Peabody College of Education and Human Development offers a variety of respected, nationally-recognized graduate programs designed with future agents of social change in mind. We foster a culture of excellence and compassion and guide you to become the best you can be — both in the classroom and beyond.

At Peabody College, you will experience

• an inclusive, welcoming community of like-minded professionals;
• the guidance of expert faculty with real-world industry experience;
• opportunities for valuable, hands-on learning experiences,
• the option of specializing depending on your specific area of interest.

Explore our monthly publication — Ideas in Action — for an inside look at how Peabody College translates discoveries into action.

Please click below to explore a few of the graduate degrees offered at Peabody College:

• Child Studies M.Ed. — a rigorous Master of Education degree that prepares students to examine the developmental, learning and social issues concerning children and that allows students to choose from one of two tracks (the Clinical and Developmental Research Track or the Applied Professional Track).
• Cognitive Psychology in Context M.S. — an impactful Master of Science program that emphasizes research design and statistical analysis to understand cognitive processes and real-world applications best, making it perfect for those interested in pursuing doctoral studies in cognitive science.
• Education Policy M.P.P — an analysis-focused Master of Public Policy program designed for future leaders in education policy and practice, allowing students to specialize in either K-12 Education Policy, Higher Education Policy or Quantitative Methods in Education Policy. 
• Quantitative Methods M.Ed. — a data-driven Master of Education degree that teaches the theory and application of quantitative analysis in behavioral, social and educational sciences.

Connect with the Community of Professionals Seeking to Enhance Humankind at Peabody College

At Peabody College, we equip you with the marketable, transferable skills needed to secure a valuable career in education and beyond. You will emerge from the graduate program of your choice ready to enhance humankind in more meaningful ways than you could have imagined.

If you want to develop the sought-after skills needed to be a force for change in the social and educational spaces, you are in the right place .

We invite you to request more information ; we will connect you with an admissions professional who can answer all your questions about choosing one of these transformative graduate degrees at Peabody College. You may also take this opportunity to review our admissions requirements and start your online application today. 

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qualitative and quantitative header

Learning Objective

Differentiate between qualitative and quantitative approaches.

Hong is a physical therapist who teaches injury assessment classes at the University of Utah. With the recent change to online for the remainder of the semester, Hong is interested in the impact on students’ skills acquisition for injury assessment. He wants to utilize both quantitative and qualitative approaches—he plans to compare previous student test scores to current student test scores. He also plans to interview current students about their experiences practicing injury assessment skills virtually. What specific study design methods will Hong use?

Making sense of the evidence

hen conducting a literature search and reviewing research articles, it is important to have a general understanding of the types of research and data you anticipate from different types of studies.

In this article, we review two broad categories of study methods, quantitative and qualitative, and discuss some of their subtypes, or designs, and the type of data that they generate.

Quantitative vs. qualitative approaches

Quantitative is measurable. It is often associated with a more traditional scientific method of gathering data in an organized, objective manner so that findings can be generalized to other persons or populations. Quantitative designs are based on probabilities or likelihood—it utilizes ‘p’ values, power analysis, and other scientific methods to ensure the rigor and reproducibility of the results to other populations. Quantitative designs can be experimental, quasi-experimental, descriptive, or correlational.

Qualitative is usually more subjective , although like quantitative research, it also uses a systematic approach. Qualitative research is generally preferred when the clinical question centers around life experiences or meaning. Qualitative research explores the complexity, depth, and richness of a particular situation from the perspective of the informants—referring to the person or persons providing the information. This may be the patient, the patient’s caregivers, the patient’s family members, etc. The information may also come from the investigator’s or researcher’s observations. At the heart of qualitative research is the belief that reality is based on perceptions and can be different for each person, often changing over time.

Study design differences

Quantitative design methods

Quantitative designs typically fall into four categories: experimental, quasi-experimental, descriptive, or correlational. Let’s talk about these different types. But before we begin, we need to briefly review the difference between independent and dependent variables.

The independent variable is the variable that is being manipulated, or the one that varies. It is sometimes called the ‘predictor’ or ‘treatment’ variable.

The dependent variable is the outcome (or response) variable. Changes in the dependent variables are presumed to be caused or influenced by the independent variable.

Experimental

In experimental designs, there are often treatment groups and control groups. This study design looks for cause and effect (if A, then B), so it requires having control over at least one of the independent, or treatment variables. Experimental design administers the treatment to some of the subjects (called the ‘experimental group’) and not to others (called the ‘control group’). Subjects are randomly assigned—meaning that they would have an equal chance of being assigned to the control group or the experimental group. This is the strongest design for testing cause and effect relationships because randomization reduces bias. In fact, most researchers believe that a randomized controlled trail is the only kind of research study where we can infer cause (if A, then B). The difficulty with a randomized controlled trial is that the results may not be generalizable in all circumstances with all patient populations, so as with any research study, you need to consider the application of the findings to your patients in your setting. 

Quasi-experimental

Quasi-Experimental studies also seek to identify a cause and effect (causal) relationship, although they are less powerful than experimental designs. This is because they lack one or more characteristics of a true experiment. For instance, they may not include random assignment or they may not have a control group. As is often the case in the ‘real world’, clinical care variables often cannot be controlled due to ethical, practical, or fiscal concerns. So, the quasi experimental approach is utilized when a randomized controlled trial is not possible. For example, if it was found that the new treatment stopped disease progression, it would no longer be ethical to withhold it from others by establishing a control group.

Descriptive

Descriptive studies give us an accurate account of the characteristics of a particular situation or group. They are often used to determine how often something occurs, the likelihood of something occurring, or to provide a way to categorize information. For example, let’s say we wanted to look at the visiting policy in the ICU and describe how implementing an open-visiting policy affected nurse satisfaction. We could use a research tool, such as a Likert scale (5 = very satisfied and 1 = very dissatisfied), to help us gain an understanding of how satisfied nurses are as a group with this policy.

Correlational

Correlational research involves the study of the relationship between two or more variables. The primary purpose is to explain the nature of the relationship, not to determine the cause and effect. For example, if you wanted to examine whether first-time moms who have an elective induction are more likely to have a cesarean birth than first-time moms who go into labor naturally, the independent variables would be ‘elective induction’ and ‘go into labor naturally’ (because they are the variables that ‘vary’) and the outcome variable is ‘cesarean section.’ Even if you find a strong relationship between elective inductions and an increased likelihood of cesarean birth, you cannot state that elective inductions ‘cause’ cesarean births because we have no control over the variables. We can only report an increased likelihood.   

Qualitative design methods

Qualitative methods delve deeply into experiences, social processes, and subcultures. Qualitative study generally falls under three types of designs: phenomenology, ethnography and grounded theory.

Phenomenology

In this approach, we want to understand and describe the lived experience or meaning of persons with a particular condition or situation. For example, phenomenological questions might ask “What is it like for an adolescent to have a younger sibling with a terminal illness?” or “What is the lived experience of caring for an older house-bound dependent parent?”

Ethnography

Ethnographic studies focus on the culture of a group of people. The assumption behind ethnographies is that groups of individuals evolve into a kind of ‘culture’ that guides the way members of that culture or group view the world. In this kind of study, the research focuses on participant observation, where the researcher becomes an active participant in that culture to understand its experiences. For example, nursing could be considered a professional culture, and the unit of a hospital can be viewed as a subculture. One example specific to nursing culture was a study done in 2006 by Deitrick and colleagues . They used ethnographic methods to examine problems related to answering patient call lights on one medical surgical inpatient unit. The single nursing unit was the ‘culture’ under study.

Grounded theory

Grounded theory research begins with a general research problem, selects persons most likely to clarify the initial understanding of the question, and uses a variety of techniques (interviewing, observation, document review to name a few) to discover and develop a theory. For example, one nurse researcher used a grounded theory approach to explain how African American women from different socioeconomic backgrounds make decisions about mammography screening. Because African American women historically have fewer mammograms (and therefore lower survival rates for later stage detection), understanding their decision-making process may help the provider support more effective health promotion efforts. 

Being able to identify the differences between qualitative and quantitative research and becoming familiar with the subtypes of each can make a literature search a little less daunting.

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This article originally appeared July 2, 2020. It was updated to reflect current practice on March 21, 2021.

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What Is Qualitative Research?

• Conducting Research
• Data Collection and Analysis

Qualitative Research Methods in Psychology

This four-and-a-half-hour course delves into the intricacies of qualitative research in psychology, emphasizing the exploration of individuals’ lived experiences through methods like interviews and observations. Rooted in historical and cross-disciplinary foundations, the course offers a rich understanding of qualitative inquiry, enriched with examples, activities, and self-assessments.

Exploring the foundations of qualitative research, we seek to understand the historical and cross-disciplinary origins of qualitative research and to explore the philosophical underpinnings and interpretive frameworks, including postpositivism, constructivism, transformative, and pragmatism.

We explore foundational research methods and techniques, emphasizing the iterative, naturalistic, and contextual facets of qualitative research. Then, we explore the concept of trustworthiness in qualitative research and four key criteria for judging the soundness of qualitative studies: credibility, transferability, dependability, and confirmability. We also address common critiques of qualitative research from a quantitative perspective and understand their misalignment with qualitative principles.

In keeping with emphases in the research literature, we explore the researcher’s role and the concept of reflexivity. The course focuses on the importance of the researcher’s closeness to participants and the impact of the researcher’s own biases and assumptions, as well as how to conduct a self-assessment for reflecting on one’s own research interests and experiences.

Principles discussed in the course are illustrated with examples from the research literature, allowing the user to gain insight into how researchers explore the lived experiences of individuals, groups, and cultures using qualitative inquiry. This course provides a deep dive into the world of qualitative research, offering tools and techniques to understand and appreciate the depth and nuance it brings to the study of human experiences.

Learning objectives

• Describe the iterative, naturalistic, and contextual facets of qualitative research.
• Examine the philosophical underpinnings and interpretive frameworks informing qualitative research.
• Explore the features of qualitative studies in psychology.
• Evaluate qualitative studies by their associated rigor criteria, which differ from criteria used to evaluate quantitative studies.
• Describe four methods to enhance the trustworthiness of qualitative studies: credibility, transferability, dependability, and confirmability.
• Discover practical strategies that promote credibility, transferability, dependability, and confirmability in qualitative studies.

This program does not offer CE credit.

Coursera works with universities and other organizations to offer online courses, certifications, and degrees in a variety of subjects.

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The use of interviewing in phenomenology, narrative inquiry, and grounded theory are introduced

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Ethnographic inquiry and case study with an examination of qualitative data analysis is covered

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Choosing the Right Research Methodology: A Guide for Researchers

• 3 minute read
• 55.9K views

Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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Qualitative vs. Quantitative Research: When to Choose What?

Research serves as a fundamental tool for gaining insights, testing hypotheses, and making informed decisions. Across industries like healthcare, automobile, mining, and telecom, research methodologies shape how we understand complex topics. Two primary research methodologies dominate the field: qualitative and quantitative. Each approach serves distinct purposes, and understanding their differences is crucial for selecting the right one for your specific research needs.

Qualitative Research

Qualitative research focuses on gathering non-numerical data and interpreting it to uncover underlying patterns, meanings, and motivations. It often involves methods like interviews, focus group discussions (FGDs) , observations, case studies, and open-ended surveys. Rather than providing hard numbers, qualitative research allows you to explore complex subjects in depth and understand people’s thoughts, behaviours, and attitudes.

When to Choose Qualitative Research

• Understanding Motivations and Behaviors: Qualitative research excels when your goal is to delve into the “why” behind actions or decisions. For instance, if you want to know why a consumer prefers one product over another, qualitative research can uncover personal preferences and emotions driving that choice.
• Exploring New Ideas: When innovation is the key, qualitative research helps generate fresh ideas. If you’re developing new products, services, or strategies, you can leverage qualitative research to identify customer pain points or preferences that might not have been previously considered.
• Gaining Insights into Complex Issues: Some issues are inherently hard to quantify, especially when dealing with human emotions, motivations, or unique social interactions. In such cases, qualitative research can shed light on nuances and layers of complexity.
• Developing a Deeper Understanding: If your focus is to obtain a richer and more detailed understanding of a subject, qualitative research can provide in-depth perspectives that quantitative methods may miss.

  Examples of Qualitative Research

• Market Research: Investigating customer experiences, feedback, or brand loyalty by conducting interviews or FGDs.
• Healthcare: Understanding patient journeys and experiences by interviewing healthcare providers and patients.
• Education: Investigating the effectiveness of teaching methods by observing classrooms or conducting interviews with educators.
• Social Sciences: Studying cultural trends and practices through ethnographic research and direct observation.

  Quantitative Research

In contrast to qualitative approaches, quantitative research focuses on numerical data. It involves structured methods like surveys , polls, and experiments, and uses statistical tools to analyze measurable data. Quantitative research answers the “what” and “how many” questions by providing objective, data-driven results.

When to Choose Quantitative Research

• Testing Hypotheses: If you want to test a specific hypothesis or theory, quantitative research can provide clear, measurable data. For instance, if you suspect that a new educational program improves student performance, conducting a controlled study and analyzing the results can provide definitive evidence.
• Measuring Outcomes: Quantitative research is ideal for determining the success or failure of interventions. In business, for example, companies may want to measure the impact of marketing strategies on sales growth through quantitative surveys and data analysis.
• Identifying Trends and Patterns: When working with large datasets, quantitative research helps detect patterns and trends. Whether you’re tracking demographic changes, economic shifts, or market behavior, numerical data provides clarity.
• Making Predictions: Quantitative research can also be used to create predictive models based on historical data. These models are particularly useful in fields like healthcare (predicting patient outcomes), finance (forecasting stock market trends), and marketing (predicting customer behavior).

  Examples of Quantitative Research

• Market Research: Surveys measuring customer satisfaction or market share.
• Healthcare: Clinical trials that evaluate the effectiveness of new treatments.
• Education: Analyzing standardized test scores to assess student performance.
• Social Sciences: Examining demographic data to understand social trends.

  Choosing the Right Method

The choice between qualitative and quantitative research depends on your research objectives. While qualitative research allows for deep exploration and understanding of complex issues, quantitative research provides data that can be statistically analyzed and generalized across larger populations.

In many cases, a combination of both approaches—known as mixed-method research—provides the most comprehensive understanding. For example, a company may start with qualitative research to explore customer opinions on a new product and then conduct a quantitative survey to measure how widespread those opinions are.

Key Factors to Consider When Choosing a Research Method:

• Research Question: What answers are you trying to get from your Research questions? Is it about understanding experiences (qualitative) or measuring results (quantitative)?
• Data Type: Do you need to collect textual, observational data (qualitative) or numerical, measurable data (quantitative)?
• Sample Size: Qualitative research often involves smaller sample sizes for in-depth exploration, while quantitative research requires larger sample sizes for statistical significance.
• Time and Resources: Consider the availability of resources, as qualitative research can be more time-intensive but offers richer insights, while quantitative research can be conducted with structured tools like surveys and requires less time for data collection.
• Research Goals: What is your end goal—understanding deeper motivations or quantifying results to guide decision-making?

  Conclusion: The Value of Combining Both Approaches

Qualitative and quantitative research methodologies each have their strengths. Qualitative research provides depth and context, while quantitative research offers breadth and generalizability. By understanding when and how to use these methods, you can design research projects that deliver the best insights.

At HBG TM , we recognize the value of both qualitative and quantitative approaches in providing comprehensive research solutions. With over 14 years of experience and a global team of experts, HBG TM offers full-service market research that covers everything from in-depth interviews to large-scale surveys. Whether you’re looking to understand customer motivations or measure the success of a business strategy, HBG’s TM tailored research solutions ensure that you achieve your research goals, powered by data-driven insights and deep understanding.

Rochana Sarkar Associate Director

Rochana Sarkar spearheads the CATI/telephonic research team at our organization, bringing over 12 years of expertise in the market research industry. As an experienced professional, she is actively involved in managing clients and devising effective strategies to deliver projects with precision and quality. In her current role, Rochana manages a large team of professionals. Her exceptional people management skills enable her to drive performance and profitability within the team, contributing significantly to the strategic growth and decision-making processes of the organization. Rochana's dedication to excellence and her deep industry knowledge make her an invaluable asset to our team.

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Everything You Need to Know about Qualitative Research

Qualitative research is a method for conducting a study that focuses on participants’ attitudes and behaviors rather than objective data. As a result, this style of research can provide valuable insight into a topic and enable scholars to consider problems from a new perspective. While there may be a general belief that qualitative research is easier than a quantitative method of inquiry, this is not entirely true. Although qualitative methods often require fewer resources and can be conducted in non-controlled settings, it is necessary to take many aspects into account to improve the quality and reliability of a qualitative study and its outcomes. This guide will provide information about using the qualitative research method to help you produce a high-quality study that will display your research skills and expertise.

Prepare a Research Question

The first task before starting your qualitative research is to construct an appropriate research question. This research method deals with variables that cannot be quantified or measured, and the research question needs to reflect this reality. For example, you might choose to investigate attitudes regarding a particular issue as one variable in your study. In addition, you would be wise to consider the following qualities of a research question:

• Clarity. Choosing a research question that is too general or broad will make research more difficult to conduct successfully.
• Complexity. Ideally, a research question should include at least two variables. Include more focus areas if desired, but make sure that the scope of research is manageable and that you can study the chosen variables using qualitative methods.
• Relevance to a particular subject area. In order to earn excellent marks on a research paper, it is critical to choose a topic related to the subject that will enable you to achieve the course objectives or learning outcomes.
• Applicability to practice. To ensure meaningful research, choose a research question that relates to a particular practice issue.

Perform a Literature Review

A thorough literature review is a prerequisite of a successful study. It provides insight into what other authors have found in their inquiries as well as errors, gaps, and limitations that could affect your research. Keep in mind a few important rules for writing an excellent literature review:

• Include reputable academic publications. These can be found in peer-reviewed research journals and conference proceedings.
• Identify common themes or problems. Reading through the material will allow you to explore the topic and improve the quality of your future study.
• Note the methods that other authors have used to research similar topics. The inquiry methods of experienced researchers might become the foundation of your methodology.
• Include reference information. Even when simply making notes, cite where you found the information to reduce the chances of accidentally plagiarizing someone’s work.

Select a Qualitative Methodology

Once you complete a literature review, you should have an idea of a qualitative methodology that you can apply in answering your research question. Some examples of methodologies used in qualitative inquiries are:

• Grounded theory: collecting and synthesizing information from previous research studies or participants’ answers
• Action research: conducting a study as a part of professional practice to solve an issue or improve operations
• Ethnography: observing people without interfering with their activities or social environment
• Phenomenology: studying a particular event or problem experienced by others

The choice of a specific methodology depends on the features of your study, the research question, and the available resources. For example, ethnography relies on observing uncontrolled behavior and thus involves the least expense compared to other research methodologies. Action research also requires few resources but is not suitable for all practice settings. Therefore, it is strongly advised that you read more about each qualitative methodology before making your selection.

Choose a Data Collection Method

Another significant part of planning a qualitative research study is choosing the correct data collection method. In qualitative studies, data collection methods may include secondary research, observations, and interviews. Once again, the choice of the appropriate data collection tool depends on the nature of your research. To check if a particular approach to data collection suits your needs, consider the following questions:

• Will this data collection method allow you to answer the research question?
• Are there any constraints involved in the chosen methods? For instance, interviews might take more time than other tools and will probably require financial investment to attract more participants.
• Was this method used in other studies on your chosen topic?
• Do you need additional resources, such as equipment or staff, to apply this method?

Answering these questions will help you to ensure that your chosen data collection tool will be beneficial to your research and will yield optimal results.

Analyze the Data Collected

The final and most crucial part of qualitative research is data analysis. It is crucial to make sure that your approach to data analysis is correct to avoid errors and false conclusions. The three main methods of analyzing qualitative data are described below:

• Coding is typically used in conjunction with grounded theory methodology. This approach involves analyzing information to discern the presence of pre-defined codes. For example, if you are studying the influence of social media on self-esteem, your terms for coding might include “poor body image,” “social anxiety,” “depression,” and other concepts related to your research question.
• Content analysis is probably the easiest approach to data analysis in qualitative research. This method involves looking at texts, such as interview transcripts, to uncover underlying themes and meanings. The content analysis approach lends itself to identifying patterns that define relationships between two or more different concepts or variables.
• Narrative analysis . In this data analysis methodology, researchers focus on analyzing each piece of information in detail to determine how the participants’ attitudes or behaviors were influenced by their life circumstances, socioeconomic or political situation, or other relevant factors. A narrative analysis also considers the participants’ speech patterns, an essential component in studying a particular group with distinctive linguistic characteristics.

Whichever data analysis approach you may choose, try to obtain as much information as you can about its application in practice. Guidelines and books on qualitative data analysis will provide you with all the information necessary to successfully analyze the data you’ve collected. You can familiarize yourself with the examples of qualitative research essays here .

Prepare a Report

Finally, once you have analyzed all the available data and arrived at a conclusion, it’s time to produce the research report. This work will usually include six sections: introduction, literature review, methodology, results, discussion, and conclusion. Optionally, you might also add a section on the limitations of your study and outline suggestions for future research on the topic. Make sure that your report is structured correctly, includes all the references used, and contains no stylistic, logical, or grammatical errors.

In all, conducting a qualitative study requires considerable work. It is essential to plan your research carefully and explore all appropriate options in terms of methodologies, data collection, and analysis tools. The recommendations in this guide will assist you throughout all stages of your research. Most importantly, staying focused on the research question and the goals of the study will help you to write a high-quality research paper and impress your instructor.

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• Volume 14, Issue 10
• Exploring the application status of qualitative studies in the research area of acupuncture: a scoping review protocol
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• http://orcid.org/0000-0001-8047-7295 Yana Xie 1 ,
• Cuiting Liu 2 ,
• Yang Fang 1 ,
• Tingting Guo 1 ,
• Ye Quan 1 ,
• Yixuan Xie 1 ,
• 1 School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine , Beijing , China
• 2 Jinhua Hospital of Traditional Chinese Medicine , Jinhua , Zhejiang , China
• 3 Guangxi University of Chinese Medicine , Nanning , Guangxi , China
• Correspondence to Jian Dai; daij{at}gxtcmu.edu.cn

Introduction With the wide development of acupuncture clinical practice, acupuncture research has been conducted worldwide, of which the most common method is quantitative study. However, research questions around acupuncture cannot always be addressed by quantitative studies due to their intrinsic characteristics. Qualitative studies can perfectly complement this knowledge gap in acupuncture research. To date, few qualitative studies on acupuncture research have been summarised. The objective of this scoping review is to review the application status of qualitative studies in the field of acupuncture research.

Methods In accordance with the framework put forward by Arksey and O'Malley, this proposed scoping review (registration DOI: https://doi.org/10.17605/OSF.IO/VYBMT ) will be applied as the following steps: (1) identifying the research questions, (2) identifying relevant studies, (3) study selection, (4) charting the data and (5) collating, summarising and reporting the results. Six databases with Google Scholar and Baidu Scholar will be searched with a comprehensive searching strategy, and two reviewers finishing uniform training and pilot test will independently screen the potential literature to include eligible ones. Endnote 20 will be used to manage the literature; a predesigned, standardised Excel sheet will be used to load all information extracted. Findings of this scoping review will be reported and described in a narrative manner. Tables, charts or figures will be used to present the results and qualitative content analysis and thematic analysis based on grounded theory will be adopted to analyse the data. We initiated our search on 13 March 2024.

Ethics and dissemination As scoping reviews are a form of secondary data analysis, ethical review is not required. Our research results will provide future research direction for qualitative studies of acupuncture and be disseminated through a peer-reviewed publication and related scientific conferences.

• Acupuncture
• Protocols & guidelines
• QUALITATIVE RESEARCH

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2024-088006

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STRENGTHS AND LIMITATIONS OF THIS STUDY

Our scoping review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and can provide a broad overview of the eligible literature.

A comprehensive search of literature is developed with the help of an experienced librarian to promote a qualified search.

To ensure a comprehensive search, an extensive review of grey literature from Google Scholar and Baidu Scholar will supplement the database search.

We will only include English and Chinese literature, so there is a probability of a selection bias.

A measurement bias might exist as the studies included will contain different study types, and they might not be fully comparable.

Introduction

With the rapid development of globalisation, acupuncture, which originated in ancient China, has now been popularly accepted and applied in 196 countries and regions worldwide. 1 Acupuncture has currently become one of the most widely used complementary and alternative medicines in the world. 2 Accordingly, with the objective to provide evidence for acupuncture efficacy and effectiveness, substantial research has been carried out, with the number of clinical trials and systematic reviews of acupuncture intervention increasing rapidly. 3 4 Without a doubt, most of the research adopted a method of quantitative study that derives from the scientific method used in the physical sciences. 5 With the characteristics of being objective, formal and systematic, quantitative studies describe, test and examine cause-and-effect relationships using a deductive process of knowledge attainment. 5 In quantitative studies, objective measurements and the statistical, mathematical or numerical analysis of data collected are emphasised to quantify or measure phenomena and produce findings. Common quantitative studies include randomised controlled studies which ensure sufficient methodological rigour, cohort, case control and cross-sectional studies as well as quantitative synthesis such as meta-analysis and cost-effectiveness analysis, etc. Although quantitative studies of acupuncture have the strength of transforming observations into objective facts, 6 they fail to capture issues related to acupuncture experiences, attitudes, beliefs, perceptions, perspectives, understandings, expectations or insights of both acupuncture patients and practitioners. This gap needs bridging; hence, qualitative studies were introduced into the area of acupuncture research. 7

Qualitative methods were defined as ‘all types of research that produces data that do not result from statistical procedures or other means of quantification’. 8 Qualitative studies aim to provide in-depth insights and understanding of real-world problems, and, in contrast to quantitative studies, they do not introduce treatments, manipulate or quantify predefined variables. 9 Qualitative studies are devoted to identifying effects/factors whose mechanisms cannot be clarified by quantitative studies. Unlike quantitative studies, seeking the causal biological mechanisms of health interventions or obtaining objective evidence of causality is not the aim of qualitative research. 6 Qualitative studies are dedicated to capturing knowledge of models of behaviours, attitudes, experiences and perceptions, as well as reasons behind behaviours, which might facilitate practices. In the area of acupuncture research, scholars attach more attention to verifying the efficacy/effectiveness of acupuncture and related interventions, such as electro-acupuncture, laser acupuncture, auricular acupuncture, etc. However, more clinical questions in the field of acupuncture needs explorations and elaboration: How do patients think of acupuncture? Why do they choose to get needled when getting sick? What do they expect from acupuncture treatments? Do their prior experiences of acupuncture influence the holistic effectiveness of treatments? What do they think of the practitioners of acupuncture? What do acupuncturists expect from the acupuncture treatments? Do the interactions between acupuncturists and patients impact the holistic effectiveness and if so, how does it work? Obviously, quantitative studies are not suitable methods to answer these questions. Instead, for these clinical questions of acupuncture, the qualitative approach may be more efficient and has the potential to expand the scope of evidence-based medicine.

It is argued that a balanced perspective of qualitative and quantitative research without considering one as superior to the other 10 should be kept. Although the data being investigated and analysed (statistical, numerical and quantitative vs humanistic, descriptive and qualitative) and methods (deductive approach vs inductive approach) being used in quantitative and qualitative studies vary, quantitative and qualitative research can still work together synergistically and complementarily. In the area of acupuncture research, qualitative studies are usually used to complement the findings from quantitative studies, such as describing patients’ perceived benefits/changes after acupuncture treatments, 11 12 assessing patients' preferences and willingness to pay for acupuncture treatment, 13 exploring patients’ acupuncture experiences and attitudes 14 as well as perspectives and considerations of acupuncturists, 15 16 etc. Besides, a mixed-methods approach with the combination of quantitative and qualitative methods is also used in acupuncture research, 17 18 attempting to grasp the holistic picture of acupuncture intervention.

To date, few qualitative studies on acupuncture research have been summarised. García-Escamilla et al and Zhang et al 19 20 conducted a thematic synthesis of health professionals’ perspectives on the integration of acupuncture into conventional/Western medicine. Jake et al 21 conducted a qualitative systematic review of patients’ experiences towards acupuncture. These efforts help us understand the attitudes of health practitioners and patients towards acupuncture specifically. However, an overview with a broader scope is needed to summarise what has been done in the qualitative studies of acupuncture. The objective of this scoping review was to review the application status of qualitative studies in the field of acupuncture research. We aimed to know that in the area of acupuncture research, what kind of methods have been adopted in the qualitative studies? What knowledge have these qualitative studies found about acupuncture? and What implications these studies bring for future acupuncture studies?

Materials and methods

Study design and registration.

This protocol for scoping review was developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for Scoping Reviews 22 and has been registered in the Open Science Framework ( https://osf.io/vybmt ) on 26 September 2023.

This proposed scoping review will be conducted in accordance with the framework put forward by Arksey and O'Malley, 23 in conjunction with the Joanna Briggs Institute methodology for scoping reviews. 24 The following processes will be applied and are described in detail as follows: (1) identifying the research questions, (2) identifying relevant studies, (3) study selection, (4) charting the data and (5) collating, summarising and reporting the results.

Stage 1: identifying the research questions

This stage is based on a preliminary literature search of published qualitative studies on acupuncture in the database PubMed. After this preparation, the research team members discussed the topic of the research questions of this scoping review and reached an agreement. The research team comprises three specialists in acupuncture, epidemiology and health statistics (YX, JD and BJ) who have profound experiences in reviews and data analysis of medicine, two PhD candidate researchers (YX and YF) and an acupuncturist (CL), as well as two postgraduate researchers of acupuncture (TG and YQ). All members of the research team agreed on the research questions. In our scoping review, we will attempt to answer the following questions:

How many qualitative studies on acupuncture research have been done and around what topic were they conducted?

What are the characteristics of these qualitative studies (including year of publication, published journals, research region, etc)?

Among these qualitative studies of acupuncture, what detailed methods of, or in what forms were they chosen to study related questions?

From all these qualitative studies, what main conclusions can be drawn, where the knowledge gaps are and what else can/is needed to be conducted to clarify more questions?

Stage 2: identifying relevant studies

Extensive discussions were involved in the development of literature search and extraction strategies. Agreement was reached among all the research team members around the most appropriate definitions, concepts and terminology relating to our research questions and objectives. This proposed scoping review will be restricted to obtaining peer-reviewed studies on qualitative studies in the area of acupuncture research. We will include related qualitative studies of which the investigated have no age restrictions. And in those studies, acupuncture could be used as both prevention and treatment.

Six electric databases, including three English databases and three Chinese databases, will be systematically searched: PubMed, Web of Science Core Collection, Embase, CNKI, Wanfang and VIP. Grey literature will also be considered by searching Google Scholar and Baidu Scholar. The search strategy will be adjusted to suit each database and further refined with professional help from an experienced librarian. This search list may be refined considering the iterative nature of the review process. Any changes in the search process will be documented and reported in the results paper. To get more comprehensive results, the reference lists of all included papers will be screened manually for additional potentially relevant studies. Authors of any inaccessible published paper will be contacted to obtain as many articles as we can. The search database and relevant strategies are provided in online supplemental file S1 . We initiated our search on 13 March 2024.

Supplemental material

Stage 3: study selection.

For the first phase, one review will apply the search strategy (including grey literature in Google Scholar and Baidu Scholar) to initiate the search, Endnote 20 (Clarivate Analytics, PA) 25 will be used to manage all the potential papers and remove duplicate literature. In the second phase, two reviewers will independently screen the titles and/or abstracts of the potential papers, full-texts will be obtained soon afterwards. In the third phase, two reviewers in charge of screening will read the full texts of all potential papers one by one until we obtain all eligible articles; reasons for exclusion will be provided in this stage. Any disagreement was resolved by discussion between the two reviewers and, if necessary, a third reviewer will be consulted to make a final decision regarding consensus. Figure 1 shows the PRISMA flow diagram 26 of the process of literature screening and selection.

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Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart. CNKI, China National Knowledge Infrastructure; VIP, China Science and Technology Journal Database.

Stage 4: charting the data

After the preliminary literature search in PubMed, the research team screened 20 eligible papers and correspondingly, determined the extracted items with consensus including (1) general information such as paper number, title, keywords, author, journal, impact factor, publication year and location; (2) information of study design such as subjects, subject being patient/doctor/others (P/D/O), sample size, sampling method, objective, qualitative method, mixed-methods or not, auxiliary methods, duration of method, duration of study, nested in randomised controlled trial or not, data analysis method and data analysis tool and (3) main findings ( table 1 ).

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Extracted items of eligible literature

A predesigned standardised Excel sheet will be used to load all information extracted from eligible literature. Any modifications to the extraction table will be recorded in the final scoping review. Two independent reviewers will accept uniform training and finish a pilot extraction of 10 eligible papers with crosschecking to ensure consistency. Both reviewers will finish the extraction of half of the literature and then crosscheck each other’s work. Any discrepancies will be discussed until reaching an agreement and, if necessary, a third review will help to reach a consensus. Authors of eligible papers will be contacted to obtain missing data if needed.

Stage 5: Collating, summarising and reporting the results

Due to the characteristics of a scoping review, a critical appraisal of the available literature is not required. 27 However, to ensure the reliability of our research results, we plan to partly adopt the Mixed Methods Appraisal Tool 28 ( online supplemental file S2 ) to evaluate the quality of eligible studies, which has been identified as useful in scoping reviews. Considering that our targeted literature mainly consists of qualitative content, we will report our results using descriptive summaries and narrative analysis. Tables, charts or figures might be the appropriate methods to present our general findings, such as the distribution of publication year, location, sample size, etc. The design of qualitative studies on acupuncture and its corresponding characteristics will be the focus of our work. Qualitative content analysis and thematic analysis 29 based on grounded theory will be applied in this procedure. The findings of the available literature will also be summarised in the text.

This scoping review, which will be an initiation in scoping review of qualitative studies on acupuncture research, is dedicated to summarise the characteristics of current qualitative studies on acupuncture. The findings of this scoping review will provide specific information for scholars to make clear of what has been done, how they were done and what else can/is needed to be done in qualitative studies of acupuncture research, facilitating better design and conducting of qualitative studies on acupuncture.

Ethics and dissemination

As this proposed scoping review is based on secondary data and do not involve any humans or animals, no formal ethical approval is required. This scoping review is planned to be published in a peer-reviewed journal and related scientific conferences.

Ethics statements

Patient consent for publication.

Not applicable.

• ↵ Acupuncture Clinical Research Methodology” preface to the Special Issue – Three major issues faced by Acupuncture Clinical Research . World J Acupunct Moxibustion 2023 ; 33 : 301 – 2 . doi:10.1016/j.wjam.2023.09.002 OpenUrl
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• ↵ PRISMA , 2022 . Available : https://prisma-statement.org/PRISMAStatement/ FlowDiagram
• Stern C , et al
• Gonzalez-Reyes A ,
• Vaismoradi M ,
• Turunen H ,

YX and CL contributed equally.

Contributors YX was involved in conceptualisation. JD was involved in funding acquisition. TG, YQ and CL were involved in the investigation. YX, YF and JD were involved in methodology. YX and BJ were involved in supervision. YX and BJ were involved in validation. YX and CL were involved in writing the original draft. YX and JD were involved in writing, reviewing and editing. JD is the guarantor.

Funding This work was supported by Guangxi University of Chinese Medicine Research Foundation for introduced PhD, grant number 2020BS020.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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• Chi square test of independence
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• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

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

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

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

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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

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

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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