qualitative vs quantitative research advantages and disadvantages

• Sep 9, 2020

Pros And Cons Of Qualitative Research vs Quantitative Research

Updated: 5 days ago

In this post, you will learn the pros and cons of qualitative research vs quantitative research along with the differences and discover how both types of research can help and be applied to different business situations from ethnographic research to online surveys.

Table of contents:

The difference between qualitative and quantitative research

Pros and cons of qualitative research, pros and cons of quantitative research, so when can qualitative and quantitative research be applied, main types of qualitative research methods, key types of quantitative research methods.

The table above shows the advantages and disadvantages of using qualitative research and quantitative research.

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The main purpose of qualitative research is to explore the in-depth behaviour, opinions and attitudes of a small group of individuals in a more open manner instead of strictly following a set of questions. These tend to be face to face in-depth interviews or focus groups, where people can discuss the subject at hand openly with guidance from the interviewer.

While quantitative research is where results can be measured by numbers, which is easy to pick up and understand for those making the decisions . These quantified results are gathered by interviewing a large group of people (from 50 running into the 1000s) that is a reflection of the whole population you are targeting. Hence with a larger sample size, statistical analysis can be applied to provide better consumer insights such as predicted behaviour, best price levels and key drivers of buyers’ decisions.

Other than exploring attitudes and behaviour in detail, qualitative research is also used to test adverts, develop concepts and new products and build a picture of the market. Whereas quantitative research is used more for market measurements such as the number of people who use a product or service, awareness, consideration, preference, segmenting the market and how likely are they to buy.

Pros of qualitative research

Explores attitudes and behaviour in-depth.

Explores attitudes and behaviour in-depth as it’s more on a personal level and can delve in detail to gain a better understanding of their views and actions to generate or examine a hypothesis in more detail.

Encourages discussion

Encourages discussion as it’s more in an open manner instead of strictly following a fixed set of questions. In this way, it gives the research some context rather than just numbers.

Flexibility

Flexibility, where the interviewer can probe and is able to ask any questions around the subject matter, they feel is relevant or had not thought of before during the discussions and can even change the setting.

Cons of qualitative research

The sample size can be an issue.

The sample size can be an issue if you are taking the opinion of 5 people out of 300 of your customers or subscribers as a generalisation.

Bias in the sample selection

Bias in the sample selection, meaning the people you are selecting to take part in the qualitative research may all have a certain opinion of the subject matter rather than a group of people with mixed views, which is more valuable particularly if they are debating with opposing views during focus groups.

Lack of privacy

Lack of privacy, if you are covering sensitive topics then people taking part may not be comfortable in sharing their thoughts and opinions of the subject with others.

Whether you are using a skilled moderator or not

It is of vital importance; the moderator is skilled and experienced in managing the conversations of groups as well as being knowledgeable enough of the subject matter to ask relevant questions that may have not been thought of.

Pros of quantitative research

Larger sample sizes.

Larger sample sizes allowing for robust analysis of the results, so you are able to make more generalisations of your target audience.

Impartiality and accuracy of data

Impartiality and accuracy of the data as it based on the survey questions for screening, grouping and other hard number facts.

Faster and easier to run

Faster and easier to run particularly online and mobile surveys , where you can see the results in real time.

Data is anonymous

Data is anonymous especially with sensitive topics through self-completion exercises like online surveys.

Offers reliable and continuous information

Offers reliable and continuous information where you can repeat the survey again and again weekly, monthly, quarterly, yearly to gain consistent trend data to help you plan ahead or investigate and address issues.

Cons of quantitative research

Limited by the set answers on a survey.

Limited by the set answers on a survey, so you are unable to go beyond that in delving in more detail the behaviours, attitudes and reasons as you do with qualitative research. This is particularly true with self-completion surveys (online), where there is no interviewer probing you even if you include a couple of open-ended questions.

Research is not carried out in their normal environment

Research is not carried out in their normal environment, so can seem artificial and controlled. Answers given by participants are claimed and may not be their actual behaviour in real life.

Unable to follow-up any answers given following completion of survey

Unable to follow-up any answers given after they have completed the survey due to the anonymity of the participants. This is especially true for validity of the findings if the results are inconclusive. Although you can ask at the end of the survey if they would like to do a follow-up survey but not all participants may agree to do so.

Generally qualitative research is used for exploratory purposes to get a picture of what is going on or examining a hypothesis that can be tested later on. Although it can be used independently through a series of depth interviews and focus groups to explore concepts such as ideas for advertising or new products.

While with quantitative research you can gather measurable results that you can draw insights from and take action where needed like there is a drop in the number of visitors to your website page, which may be tackled through redesign of the webpage or promotions.

Read this post if you want run a survey - 5 Best Survey Maker Platforms To Consider Using

Qualitative and quantitative research is best utilised when they are combined and split into phases. For example, phase 1 could be exploratory research with qualitative research and then in phase 2 this is followed up with quantitative research to test the hypothesis that came up in the first phase. A post phase of qualitative research can be applied if there has been redesigns of the concept or to identify experiences after an event.

There are advantages in combining data and information from both methods where you can reap the benefits from the advantages that both methods have as well as countering the limitations through this hybrid approach. This is achieved through:

Enrichment by identifying issues not found in quantitative research

Examination via generating a hypothesis that can be tested.

Explanation through bringing the results to life by understanding any surprising results from the quantitative data.

Below are the most popular types of research within qualitative and quantitative research that you can use to achieve your objectives and answer questions you may have.

The three key tools of qualitative research are:

Focus groups – this is where a group of 5 to 10 people at a set location or on a private online forum discuss a topic of interest who have been pre-selected via screening to take part in. These group discussions are led by a person moderating the group.

Depth interviews – are one to one interviews that are either conducted face to face, over the phone or through video conferencing apps like Skype and Zoom. This allows the participant to talk at length in a more open manner and is especially good for sensitive topics. The interviewer will use a discussion guide to follow a relatively unstructured list of topics.

Ethnography and observation – are a fly on the wall way of listening and observing the behaviour of participants in certain real environments like shopping at a supermarket. Is great to capture the actual actions of participants rather than what they claim to do in a survey.

The 3 most popular methods of quantitative research:

Online surveys – is without a doubt the most popular type of research especially amongst consumer research as it’s quick, easy to do and relatively cheap compared to other methods. The great thing with online surveys is it easily accessible for everyone to take part in whether that’s on a laptop, mobile or tablet and can be on a website or survey links through social media and email. Plus, you can check out the results in real time.

If you are interested in creating a survey, quiz or online forms you can try JotForm which is a easy to use interactive platform to set up surveys from scratch or have customisable templates to get you started with.

Also there is free eBook available called Jotform for Beginners that you can download and will explain the different features available to save time and boost productivity with all kinds of online forms for apps, stores, pdf, tables and more.

Telephone interviews – due to advancements in technology this is now used more for business to business research and interviews tend to last between 15 to 30 minutes. The advantage of this method is you have an interviewer who can probe or clarify any answers to open ended questions.

Face to face interviews – these are normally conducted in specific situations like shopping malls, exhibitions and the high street. As it’s more time consuming, costly and higher a security risk for interviewers, makes it the least popular method to use.

Social listening - is a form of secondary research where you can track, listen and respond to mentions about a brand or key topic on social media and elsewhere on the web. You can read more about it in this post - 3 Social Listening Tools To Consider

If you want to find out more how market research can help you, check out the posts below:

Market Research Online Surveys In 6 Easy Steps

How To Do A Survey: Top 10 Tips

Market Research Online: Benefits, Methods & Tools

Conversational Forms: Discover What So Good About Them

Causal Research: Definition | Advantages | Examples | Components

Top 5 Website Survey Questions About Usability

Learn how to do market research for a new business

M arket Research Meaning 101

Discover the importance of market research

Examples of Market Research Projects

The Best Methods Of Market Research

Primary Research vs Secondary Research

Quota Sampling: What Is It & How To Do It

6 Key Benefits Of Advertising Research

6 Crucial Steps Of NPD Research

TOP 4 Types Of Market Segmentation

How To Design A Good Questionnaire

Monadic Testing: All You Need To Know

Concept Testing: Examples, Types, Costs, Benefits

10 Key Benefits Of Market Research

Market Research Examples For Businesses To Succeed

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• INTRO TO MARKET RESEARCH

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Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

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Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

What is the difference between quantitative and qualitative?

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

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

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

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

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

What Is Qualitative Research?

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

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

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

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

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

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

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

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

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

Qualitative Methods

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

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

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

Here are some examples of qualitative data:

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

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

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

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

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

Qualitative Data Analysis

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

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

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

Key Features

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

Limitations of Qualitative Research

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

Advantages of Qualitative Research

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

What Is Quantitative Research?

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

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

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

Quantitative Methods

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

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

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

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

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

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

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

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

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

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

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

Quantitative Data Analysis

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

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

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

Limitations of Quantitative Research

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

Advantages of Quantitative Research

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

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

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

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

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

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

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

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

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

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

Further Information

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

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Quantitative vs. Qualitative Research in Psychology

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

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

• Key Differences

Quantitative Research Methods

Qualitative research methods.

• How They Relate

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

At a Glance

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

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

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

Qualitative Research vs. Quantitative Research

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

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

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

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

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

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

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

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

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

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

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

Quantitative methods are about measuring phenomena, not explaining them.

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

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

Basic Assumptions

Quantitative methods assume:

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

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

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

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

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

Correlation and Causation

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

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

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

Pitfalls of Quantitative Research

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

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

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

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

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

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

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

Qualitative Approaches

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

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

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

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

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

Interpretation

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

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

Relationship Between Qualitative and Quantitative Research

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

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

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

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

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

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

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

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

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

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

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

Qualitative vs. Quantitative Research in Education: Definitions

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

Generate Hypotheses with Qualitative Research

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

Form Strong Conclusions with Quantitative Research

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

Differences in Data Collection Methods

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

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

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

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

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

Qualitative Research Methods

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

Quantitative Research Methods

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

Choosing a Research Strategy

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

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

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

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

Learn How to Put Education Research into Action

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

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Introduction: Considering Qualitative, Quantitative and Mixed Methods Research

• First Online: 24 December 2020

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• Sofie Bager-Charleson 2  

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In this introduction we will explore some of the differences and similarities between quantitative and qualitative research, and dispel some of the perceived mysteries within research. We will briefly introduce some of the advantages and disadvantages of both approaches. There will also be an introduction to some of the philosophical assumptions that underpin quantitative and qualitative research methods, with specific mention made of ontological and epistemological considerations. These about the nature of existence (ontology) and how we might gain knowledge about the nature of existence (epistemology). We will explore the difference between positivist and interpretivist research, idiographic versus nomothetic, and inductive and deductive perspectives. Finally, we will also distinguish between qualitative, quantitative and mixed method s research, gaining familiarity with attempts to bridge divides between disciplines and research approaches. Throughout this book, the issue of research-supported practice will remain an underlying theme. This chapter aims to support a research-based practice, aided by considering the multiple routes into research. The chapter encourages you to familiarise yourself with approaches ranging from phenomenological experiences to more nomothetic, generalising and comparing foci like outcome measuring and random control trials (RCTs), understood with a basic knowledge of statistics. The book introduces you to a range of research, guided by interest in separate approaches but also inductive—deductive combinations, as in grounded theory together with pluralistic and mixed methods approaches, all with a shared interest in providing support in the field of mental health and emotional wellbeing. Primarily, we hope that the chapter will encourage you to start considering your own research. Enjoy!

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McBeath, A., Bager-Charleson, S. (2020). Introduction: Considering Qualitative, Quantitative and Mixed Methods Research. In: Bager-Charleson, S., McBeath, A. (eds) Enjoying Research in Counselling and Psychotherapy. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-55127-8_1

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Qualitative vs. quantitative data in research: what's the difference?

If you're reading this, you likely already know the importance of data analysis. And you already know it can be incredibly complex.

At its simplest, research and it's data can be broken down into two different categories: quantitative and qualitative. But what's the difference between each? And when should you use them? And how can you use them together?

Understanding the differences between qualitative and quantitative data is key to any research project. Knowing both approaches can help you in understanding your data better—and ultimately understand your customers better. Quick takeaways:

Quantitative research uses objective, numerical data to answer questions like "what" and "how often." Conversely, qualitative research seeks to answer questions like "why" and "how," focusing on subjective experiences to understand motivations and reasons.

Quantitative data is collected through methods like surveys and experiments and analyzed statistically to identify patterns. Qualitative data is gathered through interviews or observations and analyzed by categorizing information to understand themes and insights.

Effective data analysis combines quantitative data for measurable insights with qualitative data for contextual depth.

What is quantitative data?

Qualitative and quantitative data differ in their approach and the type of data they collect.

Quantitative data refers to any information that can be quantified — that is, numbers. If it can be counted or measured, and given a numerical value, it's quantitative in nature. Think of it as a measuring stick.

Quantitative variables can tell you "how many," "how much," or "how often."

Some examples of quantitative data :  

How many people attended last week's webinar? 

How much revenue did our company make last year? 

How often does a customer rage click on this app?

To analyze these research questions and make sense of this quantitative data, you’d normally use a form of statistical analysis —collecting, evaluating, and presenting large amounts of data to discover patterns and trends. Quantitative data is conducive to this type of analysis because it’s numeric and easier to analyze mathematically.

Computers now rule statistical analytics, even though traditional methods have been used for years. But today’s data volumes make statistics more valuable and useful than ever. When you think of statistical analysis now, you think of powerful computers and algorithms that fuel many of the software tools you use today.

Popular quantitative data collection methods are surveys, experiments, polls, and more.

Quantitative Data 101: What is quantitative data?

Take a deeper dive into what quantitative data is, how it works, how to analyze it, collect it, use it, and more.

Learn more about quantitative data →

What is qualitative data?

Unlike quantitative data, qualitative data is descriptive, expressed in terms of language rather than numerical values.

Qualitative data analysis describes information and cannot be measured or counted. It refers to the words or labels used to describe certain characteristics or traits.

You would turn to qualitative data to answer the "why?" or "how?" questions. It is often used to investigate open-ended studies, allowing participants (or customers) to show their true feelings and actions without guidance.

Some examples of qualitative data:

Why do people prefer using one product over another?

How do customers feel about their customer service experience?

What do people think about a new feature in the app?

Think of qualitative data as the type of data you'd get if you were to ask someone why they did something. Popular data collection methods are in-depth interviews, focus groups, or observation.

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What are the differences between qualitative vs. quantitative data?

When it comes to conducting data research, you’ll need different collection, hypotheses and analysis methods, so it’s important to understand the key differences between quantitative and qualitative data:

Quantitative data is numbers-based, countable, or measurable. Qualitative data is interpretation-based, descriptive, and relating to language.

Quantitative data tells us how many, how much, or how often in calculations. Qualitative data can help us to understand why, how, or what happened behind certain behaviors .

Quantitative data is fixed and universal. Qualitative data is subjective and unique.

Quantitative research methods are measuring and counting. Qualitative research methods are interviewing and observing.

Quantitative data is analyzed using statistical analysis. Qualitative data is analyzed by grouping the data into categories and themes.

As you can see, both provide immense value for any data collection and are key to truly finding answers and patterns. 

More examples of quantitative and qualitative data

You’ve most likely run into quantitative and qualitative data today, alone. For the visual learner, here are some examples of both quantitative and qualitative data: 

Quantitative data example

The customer has clicked on the button 13 times. 

The engineer has resolved 34 support tickets today. 

The team has completed 7 upgrades this month. 

14 cartons of eggs were purchased this month.

Qualitative data example

My manager has curly brown hair and blue eyes.

My coworker is funny, loud, and a good listener. 

The customer has a very friendly face and a contagious laugh.

The eggs were delicious.

The fundamental difference is that one type of data answers primal basics and one answers descriptively. 

What does this mean for data quality and analysis? If you just analyzed quantitative data, you’d be missing core reasons behind what makes a data collection meaningful. You need both in order to truly learn from data—and truly learn from your customers. 

What are the advantages and disadvantages of each?

Both types of data has their own pros and cons. 

Advantages of quantitative data

It’s relatively quick and easy to collect and it’s easier to draw conclusions from. 

When you collect quantitative data, the type of results will tell you which statistical tests are appropriate to use. 

As a result, interpreting your data and presenting those findings is straightforward and less open to error and subjectivity.

Another advantage is that you can replicate it. Replicating a study is possible because your data collection is measurable and tangible for further applications.

Disadvantages of quantitative data

Quantitative data doesn’t always tell you the full story (no matter what the perspective). 

With choppy information, it can be inconclusive.

Quantitative research can be limited, which can lead to overlooking broader themes and relationships.

By focusing solely on numbers, there is a risk of missing larger focus information that can be beneficial.

Advantages of qualitative data

Qualitative data offers rich, in-depth insights and allows you to explore context.

It’s great for exploratory purposes.

Qualitative research delivers a predictive element for continuous data.

Disadvantages of qualitative data

It’s not a statistically representative form of data collection because it relies upon the experience of the host (who can lose data).

It can also require multiple data sessions, which can lead to misleading conclusions.

The takeaway is that it’s tough to conduct a successful data analysis without both. They both have their advantages and disadvantages and, in a way, they complement each other. 

Now, of course, in order to analyze both types of data, information has to be collected first.

Let's get into the research.

Quantitative and qualitative research

The core difference between qualitative and quantitative research lies in their focus and methods of data collection and analysis. This distinction guides researchers in choosing an appropriate approach based on their specific research needs.

Using mixed methods of both can also help provide insights form combined qualitative and quantitative data.

Best practices of each help to look at the information under a broader lens to get a unique perspective. Using both methods is helpful because they collect rich and reliable data, which can be further tested and replicated.

What is quantitative research?

Quantitative research is based on the collection and interpretation of numeric data. It's all about the numbers and focuses on measuring (using inferential statistics ) and generalizing results. Quantitative research seeks to collect numerical data that can be transformed into usable statistics.

It relies on measurable data to formulate facts and uncover patterns in research. By employing statistical methods to analyze the data, it provides a broad overview that can be generalized to larger populations.

In terms of digital experience data, it puts everything in terms of numbers (or discrete data )—like the number of users clicking a button, bounce rates , time on site, and more. 

Some examples of quantitative research: 

What is the amount of money invested into this service?

What is the average number of times a button was dead clicked ?

How many customers are actually clicking this button?

Essentially, quantitative research is an easy way to see what’s going on at a 20,000-foot view. 

Each data set (or customer action, if we’re still talking digital experience) has a numerical value associated with it and is quantifiable information that can be used for calculating statistical analysis so that decisions can be made. 

You can use statistical operations to discover feedback patterns (with any representative sample size) in the data under examination. The results can be used to make predictions, find averages, test causes and effects, and generalize results to larger measurable data pools. 

Unlike qualitative methodology, quantitative research offers more objective findings as they are based on more reliable numeric data.

Quantitative data collection methods

A survey is one of the most common research methods with quantitative data that involves questioning a large group of people. Questions are usually closed-ended and are the same for all participants. An unclear questionnaire can lead to distorted research outcomes.

Similar to surveys, polls yield quantitative data. That is, you poll a number of people and apply a numeric value to how many people responded with each answer.

Experiments

An experiment is another common method that usually involves a control group and an experimental group . The experiment is controlled and the conditions can be manipulated accordingly. You can examine any type of records involved if they pertain to the experiment, so the data is extensive. 

What is qualitative research?

Qualitative research does not simply help to collect data. It gives a chance to understand the trends and meanings of natural actions. It’s flexible and iterative.

Qualitative research focuses on the qualities of users—the actions that drive the numbers. It's descriptive research. The qualitative approach is subjective, too. 

It focuses on describing an action, rather than measuring it.

Some examples of qualitative research: 

The sunflowers had a fresh smell that filled the office.

All the bagels with bites taken out of them had cream cheese.

The man had blonde hair with a blue hat.

Qualitative research utilizes interviews, focus groups, and observations to gather in-depth insights.

This approach shines when the research objective calls for exploring ideas or uncovering deep insights rather than quantifying elements.

Qualitative data collection methods

An interview is the most common qualitative research method. This method involves personal interaction (either in real life or virtually) with a participant. It’s mostly used for exploring attitudes and opinions regarding certain issues.

Interviews are very popular methods for collecting data in product design .

Focus groups

Data analysis by focus group is another method where participants are guided by a host to collect data. Within a group (either in person or online), each member shares their opinion and experiences on a specific topic, allowing researchers to gather perspectives and deepen their understanding of the subject matter.

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So which type of data is better for data analysis?

So how do you determine which type is better for data analysis ?

Quantitative data is structured and accountable. This type of data is formatted in a way so it can be organized, arranged, and searchable. Think about this data as numbers and values found in spreadsheets—after all, you would trust an Excel formula.

Qualitative data is considered unstructured. This type of data is formatted (and known for) being subjective, individualized, and personalized. Anything goes. Because of this, qualitative data is inferior if it’s the only data in the study. However, it’s still valuable. 

Because quantitative data is more concrete, it’s generally preferred for data analysis. Numbers don’t lie. But for complete statistical analysis, using both qualitative and quantitative yields the best results. 

At Fullstory, we understand the importance of data, which is why we created a behavioral data platform that analyzes customer data for better insights. Our platform delivers a complete, retroactive view of how people interact with your site or app—and analyzes every point of user interaction so you can scale.

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A perfect digital customer experience is often the difference between company growth and failure. And the first step toward building that experience is quantifying who your customers are, what they want, and how to provide them what they need.

Access to product analytics is the most efficient and reliable way to collect valuable quantitative data about funnel analysis, customer journey maps , user segments, and more.

But creating a perfect digital experience means you need organized and digestible quantitative data—but also access to qualitative data. Understanding the why is just as important as the what itself.

Fullstory's DXI platform combines the quantitative insights of product analytics with picture-perfect session replay for complete context that helps you answer questions, understand issues, and uncover customer opportunities.

Start a free 14-day trial to see how Fullstory can help you combine your most invaluable quantitative and qualitative insights and eliminate blind spots.

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Advantages & Disadvantages of Qualitative & Quantitative Research

Qualitative and Quantitative Research Methods

Selecting the best research method allows you to successfully answer a research question or test a hypothesis. Missteps at the onset of the research process may derail an otherwise promising study. Knowing the advantages and disadvantages of quantitative and qualitative methods will help you make a better decision. Both methods are quite useful depending on the type of study. Some dissertations and research studies take a mixed method approach, which incorporates qualitative and quantitative methods in different phases to obtain a broader perspective.

Quantitative Advantages

You may be very familiar with quantitative research from your science classes where you learned and practiced using the scientific method. A problem or question is examined by deductively forming a hypothesis derived from theory. Controlled, objective testing and experimentation ultimately supports or rejects your hypotheses. Each step is standardized to reduce bias when collecting and analyzing data. A big advantage of this approach is that the results are valid, reliable and generalizable to a larger population. Quantitative research is advantageous for studies that involve numbers, such as measuring achievement gaps between different groups of students or assessing the effectiveness of a new blood pressure medication.

Quantitative Disadvantages

While quantitative research methods work well in the laboratory under tightly controlled conditions, measuring phenomena like human behavior in natural settings is trickier. Survey instruments are vulnerable to errors such as mistakes in measurement and flawed sampling techniques. Another disadvantage is that quantitative research involves numbers, but some topics are too difficult to quantify in numbers. For example, constructing an effective survey with closed-ended questions about how people fall in love would be difficult.

Qualitative Advantages

Qualitative research is often used to conduct social and behavioral studies because human interactions are more complex than molecular reactions in a beaker. Subjectivity, nonrandom sampling and small sample size distinguishes qualitative research from quantitative research. A big advantage of qualitative research is the ability to deeply probe and obtain rich descriptive data about social phenomena through structured interviews, cultural immersion, case studies and observation, for instance. Examples include ethnography, narratives and grounded theory.

Qualitative Disadvantages

Qualitative studies often take more time to complete due to the pain staking nature of gathering and analyzing field notes, transcribing interviews, identifying themes and studying photographs, for instance. Studies are not easily replicable or generalizable to the general population. Conscious or unconscious bias can influence the researcher’s conclusions. Lacking rigorous scientific controls and numerical data, qualitative findings may be dismissed by some researchers as anecdotal information.

Mixed Methods

A mixed method approach capitalizes on the advantages of the quantitative and qualitative methods while offsetting the drawbacks of each. For instance, a principal interested in building rapport with parents of school children might undertake a mixed method study. First, the principal would send out a school climate survey to parents asking them to rate their satisfaction with the school and quality of instruction. After analyzing the data, the principal would identify areas needing further exploration such as parent complaints about the school’s response to bullying incidents. Focus groups could then be organized to gather qualitative information from parents to better understand their concerns.

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• Temple University: Qualitative Research: Grounded Theory: Advantages and Disadvantages

Dr. Mary Dowd is a dean of students whose job includes student conduct, leading the behavioral consultation team, crisis response, retention and the working with the veterans resource center. She enjoys helping parents and students solve problems through advising, teaching and writing online articles that appear on many sites. Dr. Dowd also contributes to scholarly books and journal articles.

Quantitative vs Qualitative Data: What’s the Difference?

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

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

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

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

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

Without further ado, let’s jump in.

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

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

What is quantitative data?

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

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

Learn more: What is quantitative data? A complete introduction

What is qualitative data?

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

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

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

What are the main differences between quantitative and qualitative data?

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

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

The difference between quantitative and qualitative data: An example

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

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

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

Quantitative data:

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

Qualitative data:

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

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

2. Different types of quantitative and qualitative data

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

Types of quantitative data (with examples)

Quantitative data is either discrete or continuous :

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

What are some real-world examples of quantitative data?

Some everyday examples of quantitative data include:

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

Types of qualitative data (with examples)

Qualitative data may be classified as nominal or ordinal :

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

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

What are some real-world examples of qualitative data?

Some examples of qualitative data include:

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

3. How are quantitative and qualitative data collected?

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

How is quantitative data generated?

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

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

How is qualitative data generated?

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

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

4. Quantitative vs qualitative data: methods of analysis

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

Quantitative data analysis

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

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

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

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

Qualitative data analysis

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

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

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

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

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

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

What are the advantages and disadvantages of quantitative data?

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

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

What are the advantages and disadvantages of qualitative data?

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

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

6. When should I use qualitative or quantitative data?

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

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

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

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

6. Quantitative vs. qualitative data: FAQ

What are the main differences between qualitative and quantitative research.

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

What are examples of qualitative and quantitative data?

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

7. Key takeaways

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

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

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

Qualitative Vs Quantitative Data (Differences, Pros And Cons)

What is qualitative and quantitative data, what are the main differences between qualitative and quantitative data, advantages and disadvantages of qualitative data, advantages and disadvantages of quantitative data, qualitative vs quantitative data: real-world examples, how can fullsession’s tools help you gather customer feedback, install your first website feedback form right now, fullsession pricing plans, faqs in relation to qualitative vs quantitative data.

Qualitative vs quantitative data. These two are the essence of data analysis, and for some, there is a clear winner. But don’t be too quick to judge.

We’ll walk through what sets these two apart—and then dig into how they work in the real world. From capturing life’s complexities through qualitative means to crunching numbers for clear-cut answers quantitatively, this is where things get interesting.

In this article, we’ll see what they mean, how they differ, and, most importantly, when to use them.

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Qualitative and quantitative data are fundamental for all kinds of research and data analysis. They both serve a good purpose and choosing one over another is tricky. Let’s see what each brings to the table.

What is Qualitative Data?

Qualitative data analysis involves examining non-numerical data to understand concepts, opinions, or experiences.

It often comes from interviews, open-ended survey responses , or observational studies focusing on the ‘why’ and ‘how’ of human behavior and experiences.

The data type provides insights that help understand the depth and complexity of the subject under study.

Examples of qualitative data questions:

• What are your main reasons for choosing our product over competitors?
• Can you describe your experience using our customer service?
• How do you feel about the latest changes we made to our software interface?

What is Quantitative Data?

Researchers work with numerical data to analyze quantitative data. It often comes from structured data sources like surveys with closed-ended questions , experiments, and statistical records.

Quantitative data analysis is used to quantify attitudes, opinions, behaviors, and other defined variables.

It often uses different statistical tools to identify patterns, trends, or correlations within the data set. Such analysis is essential for making general conclusions and predicting future trends based on the data.

Examples of quantitative data questions:

• How many hours per day do you use our product?
• On a scale of 1 to 10, how satisfied are you with our customer service?
• How often (in a month) do you encounter issues with our software interface?

Qualitative and quantitative data serve different purposes. Qualitative research is more about the individual; thus, you can create a better image of your ideal customer and profile your target audience more precisely.

However, quantitative data might be a powerful weapon if you can afford a considerable sample size, as you can collect many results and create in-depth charts.

Yet, both methods have pros and cons, and we will touch base in the next section.

Qualitative data is available through many methods, like in-depth interviews and observations in a natural setting. It offers broader pictures of human behavior and social phenomena. While qualitative studies excel in interpreting non-numerical data to provide depth and context, they could be better if used by others.

Advantages of Qualitative Data

• Qualitative data gives a more detailed view of people’s attitudes, behaviors, and experiences.
• Qualitative studies allow for flexibility in research methods since they adapt to changing behaviors.
• Gathering data in natural settings allows qualitative research to spot the complexities and nuances of real-life situations.
• The qualitative approach gives a voice to study participants and lets them express their perspectives and experiences in their own words.
•  Qualitative data is ideal for exploring new areas of research.

Disadvantages of Qualitative Data

• The interpretation of qualitative data can be highly subjective and depends on the researcher’s perspective so it can be biased.
• Due to typically smaller sample sizes and non-standardized data collection methods, the findings from qualitative studies may need to be more usable for colossal sample sizes.
• Collecting and analyzing qualitative data, such as transcribing and interpreting in-depth interviews, might be time-consuming and labor-intensive, requiring significant resources.

Quantitative data shines with its numerical nature and often contrasts with qualitative data collected through open-ended questions. Still, it has its own “place” in many research fields. It provides a strong foundation for statistical analysis and objective conclusions, but like any method, it has its own advantages and disadvantages.

Advantages of Quantitative Data

• Quantitative data offers a significant perk in statistical reliability and is known for its precise and objective analysis that can be replicated and verified.
• Quantitative data can be picked up from large populations, which makes it ideal for studies requiring a broad overview.
• Numerical data simplifies the process of comparing groups or variables. Doing that will help you make straightforward conclusions and trend analysis.
• Due to standardized feedback collection methods, results from quantitative research are often generalizable to a larger population.
•  Modern techniques for collecting quantitative data, like surveys and automated data capture, enable efficient and swift data collection

Disadvantages of Quantitative Data

• Quantitative data may need more depth and detail found in qualitative data, potentially overlooking the subtleties of human behavior and experience.
• The structured nature of quantitative data collection can be restrictive, limiting the ability to explore unanticipated phenomena during the research process.
• Without the contextual background of qualitative data, there’s a risk of misinterpreting quantitative data, significantly when complex human behaviors are reduced to numbers.

Qualitative and Quantitative data are both solid tools if you want to see how people see your product. Let’s see a couple of examples.

Qualitative Data Examples

• Customer Feedback Interviews : Gathering detailed opinions and feelings about a new product through individual interviews.
• Ethnographic Research : Observing and documenting the behaviors and interactions of a specific cultural group in their natural environment.
• Case Studies : In-depth analysis of a single event, situation, or individual to comprehensive insights into complex issues.

Quantitative Data Examples

• Survey Results : Analyzing responses from 1,000 participants on their product preferences, with 60% preferring Product A over Product B.
• Educational Achievement : Measuring students’ performance in a standardized test, where 75% scored above the national average.
• Market Analysis : Evaluating sales data to find that a particular product saw a 30% increase in sales following a marketing campaign.

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So, you’ve journeyed through the maze of qualitative vs quantitative data. You’ve seen how each has its place—qualitative with its rich, detailed narratives and quantitative with its hard numbers.

Remember this : Qualitative paints the picture; quantitative frames it. One gives depth, the other scale.

Combine them, and what do you get? A complete view—a 360-degree take on whatever’s at hand. FullSession can help you blend both, so you can really see the full picture and enjoy much better results.

What is the difference between quantitative and qualitative data?

Difference between quantitative and qualitative data: Quantitative data is numerical and used for measuring and counting, while qualitative data is descriptive and categorizing and conceptualizing.

What is an example of quantitative data?

The percentage of people in a survey who rate service as “excellent,” “good,” “average,” “poor.”

How do you determine if the data is qualitative or quantitative?

If the data can be counted or measured and expressed in numbers, it’s quantitative. In case it’s descriptive and involves characteristics that can’t be counted, it’s qualitative.

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Advantages And Disadvantages of Quantitative and Qualitative Research

Advantages and Disadvantages of Quantitative and Qualitative Research : The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. The key aim of research is to have a detailed understanding of a subject matter which can be achieved by exploration, description and explanation.

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Table of Contents

Meaning of Quantitative Research Method

Quantitative research involves the gathering of information and collection of data in quantities and numbers. It involves the observative strategy of research and uses statistics, computational methods and mathematics in developing theories.

It is purely a scientific/experimental method and does not rely on opinions. Rather this form of research is heavily based on formulating theories about events or phenomena through quantification before reaching a conclusion.

An example of Quantitative research is conducting surveys to determine the approval ratings of students in a Public University regarding the increase of tuition fees. In this scenario, one can distribute paper questionnaires, online surveys and polls to collate the figure representing the number of students who are either in agreement or in disagreement of the increase of tuition fees.

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Advantages of Quantitative Research

I. It allows you to reach an accurate conclusion no matter how large the subject matter is. Take for example the scenario above, if the number of students were 2000 in number and you want to do a research on the approval ratings annually. The approach makes it simplistic for the researcher to easily deduce the accurate conclusion no matter how fast the number of students grow.

ii. It is less time consuming since it is based on statistical analysis. Thus, researchers are not burdened by drawing out explanatory strategies to generate an outcome.

iii. Quantitative research does not focus on opinions but only on accurate data which is more reliable and concrete.

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iv. The research approach keeps the personal information anonymous. It protects the identity of the information provider. It only focuses on collection of data and people with this knowledge of identity preservation give honest opinions.

v. The research does not require a study group to be observed on a frequent basis. The problem of monitoring the subject matter to provide adequate information is eliminated by adopting this research. There is no need for  face to face conversations or time consuming cross examinations to get the data the researcher needs.

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vi. Objectivity: The objectivity of quantitative research is one of its key benefits. The foundation of quantitative research is the utilization of numerical data, which is frequently considered to be more unbiased and trustworthy than qualitative data. Statistical methods make it simple to assess numerical data, and the results can be impartially understood and extrapolated to larger populations. This makes it possible for researchers to make accurate and trustworthy findings based on actual data.

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Disadvantages of Quantitative research

I. As society grows, the opinions of people become so diversified and they are susceptible to the changes in the society when giving their opinions.

ii. There is no accurate generalisation of data the researcher received. In simpler words if for example, a researcher wants to know how many people are in support of secession in Nigeria. Qualitative research may show a large percentage in support of it but because there is no available option to revisit the data, the opinions could change in some time.

So it is an initial success but an eventual fail. Present circumstances may influence the opinions and ultimately the conclusion. It is the dynamic of society; As society evolves, so do the people’s perspectives and quantitative research does nit make provision for this dynamic.

iii. The cost of Quantitative research is relatively high. If you have ever conducted a physical or online survey which involves the distribution of questionnaires among targeted study groups, you will attest to the expensive nature of this research. Sometimes high profile firms and companies are involved which makes the research work more expensive.

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iv. Experienced researchers are usually uncertain about the eventual data: The purpose of research is to explore a subject matter and generate an accurate conclusion. What happens when the data collected do not represent the entire study group?

It becomes extremely difficult to reach a valid conclusion when the data gathered is not an accurate representation of everyone involved especially when it involves a large study group. This is one of the worries that concern expert researchers.

v. Reductionist: One of the main criticisms of quantitative research is that it can be reductionist in nature. Quantitative research often focuses on specific variables and measures, which may not capture the complexity and richness of human experiences.

It may overlook important nuances, context, and qualitative aspects of a phenomenon, leading to a limited understanding of the research topic.

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Meaning of Qualitative Research Method

This type of research involves investigating methodologies by collecting data where the researcher engages in open ended questions. This means that the researcher is more engaging in his questions and attempts to elicit the most positively accurate data from his targeted subject group.

Unlike Quantitative research, it does not quantify hypothesis by numbers or statistical measurements. Rather it has a more exploratory approach with the “ how ” and “ why ” which is more detailed than a “ yes ” or a “ no “. While Quantitative research deals with numerical figures, qualitative research deals more with words and meanings.

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Advantages of Qualitative Research

I . Due to the depth of qualitative research, subject matters can be examined on a larger scale in  greater detail.

ii . Qualitative Research has a more real feel as it deals with human experiences and observations. The researcher has a  more concrete foundation to gather accurate data. Take for instance, if there is a survey on the evaluation of academic performance in secondary schools.

A Qualitative researcher has an advantageous position in knowing the reason behind the increase or decline of academic performance by having long and stretched out conversations with the students to get a comprehensive data and accurate conclusion.

iii . The researcher can flow with the initial data by asking further questions in respect of the answers. This is not the case in other forms of research.

iv . Qualitative Research allows the researcher to provide a more generalised data notwithstanding the multiplicity of perspectives and opinions. For example if majority of the students are split concerning the reason for academic decline with half of them saying it is due to bad teaching while the other half attributes the decline to inadequate facilities, all these are different opinions which only a Qualitative researcher can accommodate to arrive at a definite conclusion.

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v . The respondents to the researcher are authentic, unfiltered and creative with their answers which promises a more accurate data.

vi. Rich and Detailed Data: One of the main advantages of qualitative research is its ability to provide rich and detailed data that captures the complexity and nuances of human experiences. Qualitative data can provide in-depth insights into the thoughts, feelings, and behaviors of individuals, and can offer a holistic understanding of the research topic.

This can provide a deeper and more nuanced understanding of social phenomena and human behavior.

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Disadvantages of Qualitative Research

I . One of the challenges in this type of research is that the collected data is purely based on open ended discussions. This makes the researcher the controlling figure as the interviewer which results to gathering of data which he may find useful or not, necessary or unnecessary because of its highly subjective nature.

ii . The researcher may become too opinionated in the subject matter which may influence his recollection of data. Hence there is likely to be error in gathering the right information.

iii . Qualitative Research takes a lot of time and effort in execution. The means of eliciting information from a subject group and analysing the data received, filtering the relevant ones from the irrelevant ones are tedious processes. This is more complex when large companies are involved in the research.

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iv . There is the possibility of lost data in the process of gathering. Qualitative Research is more demanding and requires a more meticulous approach than quantitative research. It is an enormous responsibility which non experienced researchers may have difficulty to bear.

v. Researchers must be experienced and have detailed knowledge in the subject matter in order to attain the most accurate data. This requires a special skill set and the process of searching for those researchers that fit the right caliber is not only costly but equally difficult, depending on the subject matter.

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vi. Subjectivity and Bias: The subjectivity and potential for bias of qualitative research are two of its key complaints. The interpretation and analysis of data used in qualitative research are subject to the researcher’s own biases, viewpoints, and preconceived beliefs. Given that various researchers may interpret the same data in different ways, the subjective aspect of qualitative research can have an impact on the validity and trustworthiness of the conclusions.

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In conclusion, it is worthy to note that both Quantitative and Qualitative researches are equally beneficial in the field of gathering data or information. Whether it is mathematically based or more of open ended discussions, it is imperative for a researcher to evaluate the essence of the research, the size of the target group or subject matter and the expenses involved. All these factors will guide a diligent researcher in determining the most trustworthy approach in research.

Edeh Samuel Chukwuemeka, ACMC, is a lawyer and a certified mediator/conciliator in Nigeria. He is also a developer with knowledge in various programming languages. Samuel is determined to leverage his skills in technology, SEO, and legal practice to revolutionize the legal profession worldwide by creating web and mobile applications that simplify legal research. Sam is also passionate about educating and providing valuable information to people.

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• v.56(1); 2023 Jan

Qualitative Research in Healthcare: Necessity and Characteristics

1 Department of Preventive Medicine, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea

2 Ulsan Metropolitan City Public Health Policy’s Institute, Ulsan, Korea

3 Department of Nursing, Chung-Ang University, Seoul, Korea

Eun Young Choi

4 College of Nursing, Sungshin Women’s University, Seoul, Korea

Seung Gyeong Jang

5 Department of Preventive Medicine, University of Ulsan College of Medicine, Seoul, Korea

Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields. This review aimed to provide a proper understanding of qualitative research. This review examined the characteristics of quantitative and qualitative research to help researchers select the appropriate qualitative research methodology. Qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions. Qualitative research is conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants and data collection methods, (5) data analysis and description of findings, and (6) research validation. This review can contribute to the more active use of qualitative research in healthcare, and the findings are expected to instill a proper understanding of qualitative research in researchers who review qualitative research reports and papers.

Graphical abstract

INTRODUCTION

The definition of research varies among studies and scholars, and it is difficult to devise a single definition. The Oxford English Dictionary defines research as “a careful study of a subject, especially in order to discover new facts or information about it” [ 1 ], while Webster’s Dictionary defines research as “studious inquiry or examination - especially: investigation or experimentation aimed at the discovery and interpretation of facts, revision of accepted theories or laws in the light of new facts, or practical application of such new or revised theories or laws” [ 2 ]. Moreover, research is broadly defined as the process of solving unsolved problems to broaden human knowledge [ 3 ]. A more thorough understanding of research can be gained by examining its types and reasons for conducting it.

The reasons for conducting research may include practical goals, such as degree attainment, job promotion, and financial profit. Research may be based on one’s own academic curiosity or aspiration or guided by professors or other supervisors. Academic research aims can be further divided into the following: (1) accurately describing an object or phenomenon, (2) identifying general laws and establishing well-designed theories for understanding and explaining a certain phenomenon, (3) predicting future events based on laws and theories, and (4) manipulating causes and conditions to induce or prevent a phenomenon [ 3 ].

The appropriate type of research must be selected based on the purpose and topic. Basic research has the primary purpose of expanding the existing knowledge base through new discoveries, while applied research aims to solve a real problem. Descriptive research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the variables or controlling the conditions. Experimental or analytical research attempts to identify causal relationships between variables through experiments by arbitrarily manipulating the variables or controlling the conditions [ 3 ]. In addition, research can be quantitative or qualitative, depending on the data collection and analytical methods. Quantitative research relies on statistical analyses of quantitative data obtained primarily through investigation and experiment, while qualitative research uses specific methodologies to analyze qualitative data obtained through participant observations and in-depth interviews. However, as these types of research are not polar opposites and the criteria for classifying research types are unclear, there is some degree of methodological overlap.

What is more important than differentiating types of research is identifying the appropriate type of research to gain a better understanding of specific questions and improve problems encountered by people in life. An appropriate research type or methodology is essential to apply findings reliably. However, quantitative research based on the philosophical ideas of empiricism and positivism has been the mainstay in the field of healthcare, with academic advancement achieved through the application of various statistical techniques to quantitative data [ 4 ]. In particular, there has been a tendency to treat complicated statistical techniques as more scientific and superior, with few qualitative studies in not only clinical medicine, but also primary care and social medicine, which are relatively strongly influenced by the social sciences [ 5 , 6 ].

Quantitative and qualitative research use different ways of exploring various social phenomena. Both research methodologies can be applied individually or in combination based on the research topic, with mixed quantitative and qualitative research methodologies becoming more widespread in recent years [ 7 ]. Applying these 2 methods through a virtuous cycle of integration from a complementary perspective can provide a more accurate understanding of human phenomena and solutions to real-world problems.

This review aimed to provide a proper understanding of qualitative research to assist researchers in selecting the appropriate research methodology. Specifically, this review examined the characteristics of quantitative and qualitative research, the applicability of qualitative research, and the data sources collected and analyzed in qualitative research.

COMPARISON OF QUALITATIVE AND QUANTITATIVE RESEARCH

A clearer understanding of qualitative research can be obtained by comparing qualitative and quantitative research, with which people are generally familiar [ 8 , 9 ]. Quantitative research focuses on testing the validity of hypotheses established by the researcher to identify the causal relationships of a specific phenomenon and discovering laws to predict that phenomenon ( Table 1 ). Therefore, it emphasizes controlling the influence of variables that may interfere with the process of identifying causality and laws. In contrast, qualitative research aims to discover and explore new hypotheses or theories based on a deep understanding of the meaning of a specific phenomenon. As such, qualitative research attempts to accept various environmental factors naturally. In quantitative research, importance is placed on the researcher acting as an outsider to take an objective view by keeping a certain distance from the research subject. In contrast, qualitative research encourages looking inside the research subjects to understand them deeply, while also emphasizing the need for researchers to take an intersubjective view that is formed and shared based on a mutual understanding with the research subjects.

Comparison of methodological characteristics between quantitative research and qualitative research

The data used in quantitative research can be expressed as numerical values, and data accumulated through questionnaire surveys and tests are often used in analyses. In contrast, qualitative research uses narrative data with words and images collected through participant observations, in-depth interviews, and focus group discussions used in the analyses. Quantitative research data are measured repeatedly to enhance their reliability, while the analyses of such data focus on superficial aspects of the phenomenon of interest. Qualitative research instead focuses on obtaining deep and rich data and aims to identify the specific contents, dynamics, and processes inherent within the phenomenon and situation.

There are clear distinctions in the advantages, disadvantages, and goals of quantitative and qualitative research. On one hand, quantitative research has the advantages of reliability and generalizability of the findings, and advances in data collection and analysis methods have increased reliability and generalizability. However, quantitative research presents difficulties with an in-depth analysis of dynamic phenomena that cannot be expressed by numbers alone and interpreting the results analyzed in terms numbers. On the other hand, qualitative research has the advantage of validity, which refers to how accurately or appropriately a phenomenon was measured. However, qualitative research also has the disadvantage of weak generalizability, which determines whether an observed phenomenon applies to other cases.

APPLICATIONS OF QUALITATIVE RESEARCH AND ITS USEFULNESS IN THE HEALTHCARE FIELD

Qualitative research cannot be the solution to all problems. A specific methodology should not be applied to all situations. Therefore, researchers need to have a good understanding of the applicability of qualitative research. Generally, qualitative research is applicable in following cases: (1) when an exploratory approach is required on a topic that is not well known, (2) when something cannot be explained fully with quantitative research, (3) when it is necessary to newly present a specific view on a research topic that is difficult to explain with existing views, (4) when it is inappropriate to present the rationale or theoretical proposition for designing hypotheses, as in quantitative research, and (5) when conducting research that requires detailed descriptive writing with literary expressions [ 7 ]. In particular, qualitative research is useful for opening new fields of research, such as important topics that have not been previously examined or whose significance has not been recognized. Moreover, qualitative research is advantageous for examining known topics from a fresh perspective.

In the healthcare field, qualitative research is conducted on various topics considering its characteristics and strengths. Quantitative research, which focuses on hypothesis validation, such as the superiority of specific treatments or the effectiveness of specific policies, and the generalization of findings, has been the primary research methodology in the field of healthcare. Qualitative research has been mostly applied for studies such as subjective disease experiences and attitudes with respect to health-related patient quality of life [ 10 - 12 ], experiences and perceptions regarding the use of healthcare services [ 13 - 15 ], and assessments of the quality of care [ 16 , 17 ]. Moreover, qualitative research has focused on vulnerable populations, such as the elderly, children, disabled [ 18 - 20 ], minorities, and socially underprivileged with specific experiences [ 21 , 22 ].

For instance, patient safety is considered a pillar of quality of care, which is an aspect of healthcare with increasing international interest. The ultimate goal of patient safety research should be the improvement of patient safety, for which it is necessary to identify the root causes of potential errors and adverse events. In such cases, qualitative rather than quantitative research is often required. It is also important to identify whether there are any barriers when applying measures for enhancing patient safety to clinical practice. To identify such barriers, qualitative research is necessary to observe healthcare workers directly applying the solutions step-by-step during each process, determine whether there are difficulties in applying the solutions to relevant stakeholders, and ask how to improve the process if there are difficulties.

Patient safety is a very broad topic, and patient safety issues could be categorized into preventing, recognizing, and responding to patient safety issues based on related metrics [ 23 ]. Responding to issues that pertain to the handling of patient safety incidents that have already occurred has received relatively less interest than other categories of research on this topic, particularly in Korea. Until 2017, almost no research was conducted on the experiences of and difficulties faced by patients and healthcare workers who have been involved in patient safety incidents. This topic can be investigated using qualitative research.

A study in Korea investigated the physical and mental suffering experienced during the process of accepting disability and medical litigation by a patient who became disabled due to medical malpractice [ 21 ]. Another qualitative case study was conducted with participants who lost a family member due to a medical accident and identified psychological suffering due to the incident, as well as secondary psychological suffering during the medical litigation process, which increased the expandability of qualitative research findings [ 24 ]. A quantitative study based on these findings confirmed that people who experienced patient safety incidents had negative responses after the incidents and a high likelihood of sleep or eating disorders, depending on their responses [ 25 ].

A study that applied the grounded theory to examine the second victim phenomenon, referring to healthcare workers who have experienced patient safety incidents, and presented the response stages experienced by second victims demonstrated the strength of qualitative research [ 26 ]. Subsequently, other studies used questionnaire surveys on physicians and nurses to quantify the physical, mental, and work-related difficulties experienced by second victims [ 27 , 28 ]. As such, qualitative research alone can produce significant findings; however, combining quantitative and qualitative research produces a synergistic effect. In the healthcare field, which remains unfamiliar with qualitative research, combining these 2 methodologies could both enhance the validity of research findings and facilitate open discussions with other researchers [ 29 ].

In addition, qualitative research has been used for diverse sub-topics, including the experiences of patients and guardians with respect to various diseases (such as cancer, myocardial infarction, chronic obstructive pulmonary disease, depression, falls, and dementia), awareness of treatment for diabetes and hypertension, the experiences of physicians and nurses when they come in contact with medical staff, awareness of community health environments, experiences of medical service utilization by the general public in medically vulnerable areas, the general public’s awareness of vaccination policies, the health issues of people with special types of employment (such as delivery and call center workers), and the unmet healthcare needs of persons with vision or hearing impairment.

GENERAL WORKFLOW OF QUALITATIVE RESEARCH

Rather than focusing on deriving objective information, qualitative research aims to discern the quality of a specific phenomenon, obtaining answers to “why” and “how” questions. Qualitative research aims to collect data multi-dimensionally and provide in-depth explanations of the phenomenon being researched. Ultimately, the purpose of qualitative research is set to help researchers gain an understanding of the research topic and reveal the implications of the research findings. Therefore, qualitative research is generally conducted in the following order: (1) selection of a research topic and question, (2) selection of a theoretical framework and methods, (3) literature analysis, (4) selection of the research participants (or participation target) and data collection methods, (5) data analysis and description of findings, and (6) research validation ( Figure 1 ) [ 30 ]. However, unlike quantitative research, in which hypothesis setting and testing take place unidirectionally, a major characteristic of qualitative research is that the process is reversible and research methods can be modified. In other words, the research topic and question could change during the literature analysis process, and theoretical and analytical methods could change during the data collection process.

General workflow of qualitative research.

Selection of a Research Topic and Question

As with any research, the first step in qualitative research is the selection of a research topic and question. Qualitative researchers can select a research topic based on their interests from daily life as a researcher, their interests in issues within the healthcare field, and ideas from the literature, such as academic journals. The research question represents a more specific aspect of the research topic. Before specifically starting to conduct research based on a research topic, the researcher should clarify what is being researched and determine what research would be desirable. When selecting a research topic and question, the research should ask: is the research executable, are the research topic and question worth researching, and is this a research question that a researcher would want to research?

Selection of Theoretical Framework and Methods

A theoretical framework refers to the thoughts or attitudes that a researcher has about the phenomenon being researched. Selecting the theoretical framework first could help qualitative researchers not only in selecting the research purpose and problem, but also in carrying out various processes, including an exploration of the precedent literature and research, selection of the data type to be collected, data analysis, and description of findings. In qualitative research, theoretical frameworks are based on philosophical ideas, which affect the selection of specific qualitative research methods. Representative qualitative research methods include the grounded theory, which is suitable for achieving the goal of developing a theory that can explain the processes involved in the phenomenon being researched; ethnographic study, which is suitable for research topics that attempt to identify and interpret the culture of a specific group; phenomenology, which is suitable for research topics that attempt to identify the nature of research participants’ experiences or the phenomenon being researched; case studies, which aim to gain an in-depth understanding of a case that has unique characteristics and can be differentiated from other cases; action research, which aims to find solutions to problems faced by research participants, with the researchers taking the same position as the participants; and narrative research, which is suitable for research topics that attempt to interpret the entire life or individual experiences contained within the stories of research participants. Other methodologies include photovoice research, consensual qualitative research, and auto-ethnographic research.

Literature Analysis

Literature analysis results can be helpful in specifically selecting the research problem, theoretical framework, and research methods. The literature analysis process compels qualitative researchers to contemplate the new knowledge that their research will add to the academic field. A comprehensive literature analysis is encouraged both in qualitative and quantitative research, and if the prior literature related to the subject to be studied is insufficient, it is sometimes evaluated as having low research potential or research value. Some have claimed that a formal literature review should not be performed before the collection of field data, as it could create bias, thereby interfering with the investigation. However, as the qualitative research process is cyclic rather than unidirectional, the majority believes that a literature review can be performed at any time. Moreover, an ethical review prior to starting the research is a requirement; therefore, the research protocol must be prepared and submitted for review and approval prior to conducting the research. To prepare research protocols, the existing literature must be analyzed at least to a certain degree. Nonetheless, qualitative researchers must keep in mind that their emotions, bias, and expectations may interject themselves during the literature review process and should strive to minimize any bias to ensure the validity of the research.

Selection of the Research Participants and Data Collection Methods

The subjects of qualitative research are not necessarily humans. It is more important to find the research subject(s) from which the most in-depth answers to the research problem can be obtained. However, the subjects in most qualitative studies are humans, as most research question focus on humans. Therefore, it is important to obtain research participants with sufficient knowledge, experience, and attitudes to provide the most appropriate answers to the research question. Quantitative research, which views generalizability as a key research goal, emphasizes the selection of research participants (i.e., the research sample that can represent the study’s population of interest), whereas qualitative research emphasizes finding research participants who can best describe and demonstrate the phenomenon of interest.

In qualitative research, the participant selection method is referred to as purposeful sampling (or purposive sampling), which can be divided into various types. Sampling methods have various advantages, disadvantages, and characteristics. For instance, unique sampling (extreme case sampling) has the advantage of being able to obtain interesting research findings by researching phenomena that have previously received little or no interest, and the disadvantage of deriving research findings that are interesting to only some readers if the research is conducted on an overly unique situation. Maximum variation sampling, also referred to as theoretical sampling, is commonly used in qualitative research based on the grounded theory. Selecting the appropriate participant sampling method that suits the purpose of research is crucial ( Table 2 ).

Sampling methods of selecting research participants in qualitative research

Once the researcher has decided how to select study participants, the data collection methods must be determined. Just as with participant sampling, various data collection methods are available, all of which have various advantages and disadvantages; therefore, the method must be selected based on the research question and circumstances. Unlike quantitative research, which usually uses a single data source and data collection method, the use of multiple data sources and data collection methods is encouraged in qualitative research [ 30 ]. Using a single data source and data collection method could cause data collection to be skewed by researcher bias; therefore, using multiple data sources and data collection methods is ideal. In qualitative research, the following data types are commonly used: (1) interview data obtained through one-on-one in-depth interviews and focus group discussions, (2) observational data from various observation levels, (3) documented data collected from personal or public documents, and (4) image data, such as photographs and videos.

Interview data are the most commonly used data source in qualitative research [ 31 ]. In qualitative research, an interview refers to communication that takes place based on a clear sense of purpose of acquiring certain information, unlike conversations that typically take place in daily life. The level of data acquired through interviews varies significantly depending on the researcher’s personal qualifications and abilities, as well as his or her level of interest and knowledge regarding the research topic. Therefore, interviewers must be trained to go beyond simply identifying the clearly expressed experiences of research participants to exploring their inner experiences and emotions [ 32 ]. Interview data can be classified based on the level of structuralization of the data collection method, sample size, and interview method. The characteristics of each type of interview are given in Table 3 .

Detailed types of interview methods according to the characteristics of in-depth interviews and focus group discussion

Observations, which represent a key data collection method in anthropology, refer to a series of actions taken by the researcher in search of a deep understanding by systematically examining the appearances of research participants that take place in natural situations [ 33 ]. Observations can be categorized as participant and non-participant, insider and outsider, disguised and undisguised, short- and long-term, and structured and unstructured. However, a line cannot be drawn clearly to differentiate these categories, and the degree of each varies along a single spectrum. Therefore, it is necessary for a qualitative researcher to select the appropriate data collection method based on the circumstances and characteristics of the research topic.

Various types of document data can be used in qualitative research. Personal documents include diaries, letters, and autobiographies, while public documents include legal documents, public announcements, and civil documents. Online documents include emails and blog or bulletin board postings, while other documents include graffiti. All these document types may be used as data sources in qualitative research. In addition, image data acquired by the research participant or researcher, such as photographs and videos, serve as useful data sources in qualitative research. Such data sources are relatively objective and easily accessible, while they contain a significant amount of qualitative meaning despite the low acquisition cost. While some data may have been collected for research purposes, other data may not have been originally produced for research. Therefore, the researcher must not distort the original information contained in the data source and must verify the accuracy and authenticity of the data source in advance [ 30 ].

This review examined the characteristics of qualitative research to help researchers select the appropriate qualitative research methodology and identify situations suitable for qualitative research in the healthcare field. In addition, this paper analyzed the selection of the research topic and problem, selection of the theoretical framework and methods, literature analysis, and selection of the research participants and data collection methods. A forthcoming paper will discuss more specific details regarding other qualitative research methodologies, such as data analysis, description of findings, and research validation. This review can contribute to the more active use of qualitative research in the healthcare field, and the findings are expected to instill a proper understanding of qualitative research in researchers who review and judge qualitative research reports and papers.

Ethics Statement

Since this study used secondary data source, we did not seek approval from the institutional review board. We also did not have to ask for the consent of the participants.

Acknowledgments

CONFLICT OF INTEREST

The authors have no conflicts of interest associated with the material presented in this paper.

AUTHOR CONTRIBUTIONS

Conceptualization: Pyo J, Lee W, Choi EY, Jang SG, Ock M. Data curation: Pyo J, Ock M. Formal analysis: Pyo J, Ock M. Funding acquisition: None. Validation: Lee W, Choi EY, Jang SG. Writing - original draft: Pyo J, Ock M. Writing - review & editing: Pyo J, Lee W, Choi EY, Jang SG, Ock M.

23 Advantages and Disadvantages of Qualitative Research

Investigating methodologies. Taking a closer look at ethnographic, anthropological, or naturalistic techniques. Data mining through observer recordings. This is what the world of qualitative research is all about. It is the comprehensive and complete data that is collected by having the courage to ask an open-ended question.

Print media has used the principles of qualitative research for generations. Now more industries are seeing the advantages that come from the extra data that is received by asking more than a “yes” or “no” question.

The advantages and disadvantages of qualitative research are quite unique. On one hand, you have the perspective of the data that is being collected. On the other hand, you have the techniques of the data collector and their own unique observations that can alter the information in subtle ways.

That’s why these key points are so important to consider.

What Are the Advantages of Qualitative Research?

1. Subject materials can be evaluated with greater detail. There are many time restrictions that are placed on research methods. The goal of a time restriction is to create a measurable outcome so that metrics can be in place. Qualitative research focuses less on the metrics of the data that is being collected and more on the subtleties of what can be found in that information. This allows for the data to have an enhanced level of detail to it, which can provide more opportunities to glean insights from it during examination.

2. Research frameworks can be fluid and based on incoming or available data. Many research opportunities must follow a specific pattern of questioning, data collection, and information reporting. Qualitative research offers a different approach. It can adapt to the quality of information that is being gathered. If the available data does not seem to be providing any results, the research can immediately shift gears and seek to gather data in a new direction. This offers more opportunities to gather important clues about any subject instead of being confined to a limited and often self-fulfilling perspective.

3. Qualitative research data is based on human experiences and observations. Humans have two very different operating systems. One is a subconscious method of operation, which is the fast and instinctual observations that are made when data is present. The other operating system is slower and more methodical, wanting to evaluate all sources of data before deciding. Many forms of research rely on the second operating system while ignoring the instinctual nature of the human mind. Qualitative research doesn’t ignore the gut instinct. It embraces it and the data that can be collected is often better for it.

4. Gathered data has a predictive quality to it. One of the common mistakes that occurs with qualitative research is an assumption that a personal perspective can be extrapolated into a group perspective. This is only possible when individuals grow up in similar circumstances, have similar perspectives about the world, and operate with similar goals. When these groups can be identified, however, the gathered individualistic data can have a predictive quality for those who are in a like-minded group. At the very least, the data has a predictive quality for the individual from whom it was gathered.

5. Qualitative research operates within structures that are fluid. Because the data being gathered through this type of research is based on observations and experiences, an experienced researcher can follow-up interesting answers with additional questions. Unlike other forms of research that require a specific framework with zero deviation, researchers can follow any data tangent which makes itself known and enhance the overall database of information that is being collected.

6. Data complexities can be incorporated into generated conclusions. Although our modern world tends to prefer statistics and verifiable facts, we cannot simply remove the human experience from the equation. Different people will have remarkably different perceptions about any statistic, fact, or event. This is because our unique experiences generate a different perspective of the data that we see. These complexities, when gathered into a singular database, can generate conclusions with more depth and accuracy, which benefits everyone.

7. Qualitative research is an open-ended process. When a researcher is properly prepared, the open-ended structures of qualitative research make it possible to get underneath superficial responses and rational thoughts to gather information from an individual’s emotional response. This is critically important to this form of researcher because it is an emotional response which often drives a person’s decisions or influences their behavior.

8. Creativity becomes a desirable quality within qualitative research. It can be difficult to analyze data that is obtained from individual sources because many people subconsciously answer in a way that they think someone wants. This desire to “please” another reduces the accuracy of the data and suppresses individual creativity. By embracing the qualitative research method, it becomes possible to encourage respondent creativity, allowing people to express themselves with authenticity. In return, the data collected becomes more accurate and can lead to predictable outcomes.

9. Qualitative research can create industry-specific insights. Brands and businesses today need to build relationships with their core demographics to survive. The terminology, vocabulary, and jargon that consumers use when looking at products or services is just as important as the reputation of the brand that is offering them. If consumers are receiving one context, but the intention of the brand is a different context, then the miscommunication can artificially restrict sales opportunities. Qualitative research gives brands access to these insights so they can accurately communicate their value propositions.

10. Smaller sample sizes are used in qualitative research, which can save on costs. Many qualitative research projects can be completed quickly and on a limited budget because they typically use smaller sample sizes that other research methods. This allows for faster results to be obtained so that projects can move forward with confidence that only good data is able to provide.

11. Qualitative research provides more content for creatives and marketing teams. When your job involves marketing, or creating new campaigns that target a specific demographic, then knowing what makes those people can be quite challenging. By going through the qualitative research approach, it becomes possible to congregate authentic ideas that can be used for marketing and other creative purposes. This makes communication between the two parties to be handled with more accuracy, leading to greater level of happiness for all parties involved.

12. Attitude explanations become possible with qualitative research. Consumer patterns can change on a dime sometimes, leaving a brand out in the cold as to what just happened. Qualitative research allows for a greater understanding of consumer attitudes, providing an explanation for events that occur outside of the predictive matrix that was developed through previous research. This allows the optimal brand/consumer relationship to be maintained.

What Are the Disadvantages of Qualitative Research?

1. The quality of the data gathered in qualitative research is highly subjective. This is where the personal nature of data gathering in qualitative research can also be a negative component of the process. What one researcher might feel is important and necessary to gather can be data that another researcher feels is pointless and won’t spend time pursuing it. Having individual perspectives and including instinctual decisions can lead to incredibly detailed data. It can also lead to data that is generalized or even inaccurate because of its reliance on researcher subjectivisms.

2. Data rigidity is more difficult to assess and demonstrate. Because individual perspectives are often the foundation of the data that is gathered in qualitative research, it is more difficult to prove that there is rigidity in the information that is collective. The human mind tends to remember things in the way it wants to remember them. That is why memories are often looked at fondly, even if the actual events that occurred may have been somewhat disturbing at the time. This innate desire to look at the good in things makes it difficult for researchers to demonstrate data validity.

3. Mining data gathered by qualitative research can be time consuming. The number of details that are often collected while performing qualitative research are often overwhelming. Sorting through that data to pull out the key points can be a time-consuming effort. It is also a subjective effort because what one researcher feels is important may not be pulled out by another researcher. Unless there are some standards in place that cannot be overridden, data mining through a massive number of details can almost be more trouble than it is worth in some instances.

4. Qualitative research creates findings that are valuable, but difficult to present. Presenting the findings which come out of qualitative research is a bit like listening to an interview on CNN. The interviewer will ask a question to the interviewee, but the goal is to receive an answer that will help present a database which presents a specific outcome to the viewer. The goal might be to have a viewer watch an interview and think, “That’s terrible. We need to pass a law to change that.” The subjective nature of the information, however, can cause the viewer to think, “That’s wonderful. Let’s keep things the way they are right now.” That is why findings from qualitative research are difficult to present. What a research gleans from the data can be very different from what an outside observer gleans from the data.

5. Data created through qualitative research is not always accepted. Because of the subjective nature of the data that is collected in qualitative research, findings are not always accepted by the scientific community. A second independent qualitative research effort which can produce similar findings is often necessary to begin the process of community acceptance.

6. Researcher influence can have a negative effect on the collected data. The quality of the data that is collected through qualitative research is highly dependent on the skills and observation of the researcher. If a researcher has a biased point of view, then their perspective will be included with the data collected and influence the outcome. There must be controls in place to help remove the potential for bias so the data collected can be reviewed with integrity. Otherwise, it would be possible for a researcher to make any claim and then use their bias through qualitative research to prove their point.

7. Replicating results can be very difficult with qualitative research. The scientific community wants to see results that can be verified and duplicated to accept research as factual. In the world of qualitative research, this can be very difficult to accomplish. Not only do you have the variability of researcher bias for which to account within the data, but there is also the informational bias that is built into the data itself from the provider. This means the scope of data gathering can be extremely limited, even if the structure of gathering information is fluid, because of each unique perspective.

8. Difficult decisions may require repetitive qualitative research periods. The smaller sample sizes of qualitative research may be an advantage, but they can also be a disadvantage for brands and businesses which are facing a difficult or potentially controversial decision. A small sample is not always representative of a larger population demographic, even if there are deep similarities with the individuals involve. This means a follow-up with a larger quantitative sample may be necessary so that data points can be tracked with more accuracy, allowing for a better overall decision to be made.

9. Unseen data can disappear during the qualitative research process. The amount of trust that is placed on the researcher to gather, and then draw together, the unseen data that is offered by a provider is enormous. The research is dependent upon the skill of the researcher being able to connect all the dots. If the researcher can do this, then the data can be meaningful and help brands and progress forward with their mission. If not, there is no way to alter course until after the first results are received. Then a new qualitative process must begin.

10. Researchers must have industry-related expertise. You can have an excellent researcher on-board for a project, but if they are not familiar with the subject matter, they will have a difficult time gathering accurate data. For qualitative research to be accurate, the interviewer involved must have specific skills, experiences, and expertise in the subject matter being studied. They must also be familiar with the material being evaluated and have the knowledge to interpret responses that are received. If any piece of this skill set is missing, the quality of the data being gathered can be open to interpretation.

11. Qualitative research is not statistically representative. The one disadvantage of qualitative research which is always present is its lack of statistical representation. It is a perspective-based method of research only, which means the responses given are not measured. Comparisons can be made and this can lead toward the duplication which may be required, but for the most part, quantitative data is required for circumstances which need statistical representation and that is not part of the qualitative research process.

The advantages and disadvantages of qualitative research make it possible to gather and analyze individualistic data on deeper levels. This makes it possible to gain new insights into consumer thoughts, demographic behavioral patterns, and emotional reasoning processes. When a research can connect the dots of each information point that is gathered, the information can lead to personalized experiences, better value in products and services, and ongoing brand development.

10 Advantages & Disadvantages of Quantitative Research

Quantitative research is a powerful tool for those looking to gather empirical data about their topic of study. Using statistical models and math, researchers evaluate their hypothesis.

Quantitative Research

When researchers look at gathering data, there are two types of testing methods they can use: quantitative research, or qualitative research. Quantitative research looks to capture real, measurable data in the form of numbers and figures; whereas qualitative research is concerned with recording opinion data, customer characteristics, and other non-numerical information.

Quantitative research is a powerful tool for those looking to gather empirical data about their topic of study. Using statistical models and math, researchers evaluate their hypothesis. An integral component of quantitative research - and truly, all research - is the careful and considered analysis of the resulting data points.

There are several key advantages and disadvantages to conducting quantitative research that should be considered when deciding which type of testing best fits the occasion.

5 Advantages of Quantitative Research

• Quantitative research is concerned with facts & verifiable information.

Quantitative research is primarily designed to capture numerical data - often for the purpose of studying a fact or phenomenon in their population. This kind of research activity is very helpful for producing data points when looking at a particular group - like a customer demographic. All of this helps us to better identify the key roots of certain customer behaviors. 

Businesses who research their customers intimately often outperform their competitors. Knowing the reasons why a customer makes a particular purchasing decision makes it easier for companies to address issues in their audiences. Data analysis of this kind can be used for a wide range of applications, even outside the world of commerce. 

• Quantitative research can be done anonymously. 

Unlike qualitative research questions - which often ask participants to divulge personal and sometimes sensitive information - quantitative research does not require participants to be named or identified. As long as those conducting the testing are able to independently verify that the participants fit the necessary profile for the test, then more identifying information is unnecessary. 

• Quantitative research processes don't need to be directly observed.

Whereas qualitative research demands close attention be paid to the process of data collection, quantitative research data can be collected passively. Surveys, polls, and other forms of asynchronous data collection generate data points over a defined period of time, freeing up researchers to focus on more important activities. 

• Quantitative research is faster than other methods.

Quantitative research can capture vast amounts of data far quicker than other research activities. The ability to work in real-time allows analysts to immediately begin incorporating new insights and changes into their work - dramatically reducing the turn-around time of their projects. Less delays and a larger sample size ensures you will have a far easier go of managing your data collection process.

• Quantitative research is verifiable and can be used to duplicate results.

The careful and exact way in which quantitative tests must be designed enables other researchers to duplicate the methodology. In order to verify the integrity of any experimental conclusion, others must be able to replicate the study on their own. Independently verifying data is how the scientific community creates precedent and establishes trust in their findings.

5 Disadvantages of Quantitative Research

• Limited to numbers and figures.

Quantitative research is an incredibly precise tool in the way that it only gathers cold hard figures. This double edged sword leaves the quantitative method unable to deal with questions that require specific feedback, and often lacks a human element. For questions like, “What sorts of emotions does our advertisement evoke in our test audiences?” or “Why do customers prefer our product over the competing brand?”, using the quantitative research method will not derive a meaningful answer.

• Testing models are more difficult to create.

Creating a quantitative research model requires careful attention to be paid to your design. From the hypothesis to the testing methods and the analysis that comes after, there are several moving parts that must be brought into alignment in order for your test to succeed. Even one unintentional error can invalidate your results, and send your team back to the drawing board to start all over again.

• Tests can be intentionally manipulative.  

Bad actors looking to push an agenda can sometimes create qualitative tests that are faulty, and designed to support a particular end result. Apolitical facts and figures can be turned political when given a limited context. You can imagine an example in which a politician devises a poll with answers that are designed to give him a favorable outcome - no matter what respondents pick.

• Results are open to subjective interpretation.

Whether due to researchers' bias or simple accident, research data can be manipulated in order to give a subjective result. When numbers are not given their full context, or were gathered in an incorrect or misleading way, the results that follow can not be correctly interpreted. Bias, opinion, and simple mistakes all work to inhibit the experimental process - and must be taken into account when designing your tests. 

• More expensive than other forms of testing. 

Quantitative research often seeks to gather large quantities of data points. While this is beneficial for the purposes of testing, the research does not come free. The grander the scope of your test and the more thorough you are in it’s methodology, the more likely it is that you will be spending a sizable portion of your marketing expenses on research alone. Polling and surveying, while affordable means of gathering quantitative data, can not always generate the kind of quality results a research project necessitates. 

Key Takeaways 

Numerical data is a vital component of almost any research project. Quantitative data can provide meaningful insight into qualitative concerns. Focusing on the facts and figures enables researchers to duplicate tests later on, and create their own data sets.

To streamline your quantitative research process:

Have a plan. Tackling your research project with a clear and focused strategy will allow you to better address any errors or hiccups that might otherwise inhibit your testing. 

Define your audience. Create a clear picture of your target audience before you design your test. Understanding who you want to test beforehand gives you the ability to choose which methodology is going to be the right fit for them. 

Test, test, and test again. Verifying your results through repeated and thorough testing builds confidence in your decision making. It’s not only smart research practice - it’s good business.

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Qualitative vs. quantitative data

Removing bias in employee evaluations with actionable data-driven metrics.

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By Joe Locke, AAS; Kelly Wright, MS

The benefits of using data to make decisions and drive change outweigh the costs of collection or analysis. Data is impartial, objective and emotionless, and it transforms into information only with context.

Care must be taken to ensure that data is not sought to support or disprove a hypothesis; instead, the data itself leads to conclusions that can be recreated empirically to validate that hypothesis. Empirical research – based on observations and experiences, rather than theory or belief – takes one of two forms: qualitative or quantitative .

Qualitative data

In qualitative research, observations or judgments are made about a thing or action, which are recorded as descriptive words. Examples include condition (e.g., good, fair, poor) or risk severity (e.g., low, moderate, high, critical).

From an analytic perspective, it is difficult to measure or rank qualitative data against other qualitative data because of the subjectivity of the criteria being used – who decides what is good, fair or poor?

Quantitative data

Opposingly, quantitative research is empirical research in which data is in the form of numbers and lends itself well to comparative analysis.

Converting qualitative judgments into quantitative data is a powerful analysis tool, making it possible to generate meaningful, actionable information.

Evaluating employee performance

Without the ability to convert qualitative data to quantitative data, it can be easy for intentional or unconscious bias to be introduced into a qualitative assessment like employee performance. Assessment of employee performance based on metrics is increasingly common as it enables employers to empirically quantify how well or poorly an employee performs with data in the form of numbers. When the employee is an EMS provider and poor performance could potentially affect patient outcomes, it is vital that an organization’s leadership implements impartial assessment and objectivity when assessing work quality.

If strict adherence to the data collection methodology is not maintained, outcomes can be manipulated to favor or disfavor individuals through intent or negligence, potentially perpetuating harmful systemic power structures. Organizations look toward data-driven metrics to evaluate individual and team performance to prevent inklings of nepotism or favoritism and promote transparency and accountability across a group. This provides leadership with concrete data-turned-actionable information to provide critical feedback to individual EMS providers, suggestions for improvement across the department, or opportunities to redefine the assessment criteria if results are inconclusive or irrelevant.

The knowledge that these assessments are being performed department-wide can lessen the sting of constructive criticism at the individual level, offer the EMS provider concrete steps to improve patient outcomes, help the department recognize appropriate EMS billing for services provided, and engender a feeling of responsibility and place within the organization.

About the authors Joe Locke, AAS, is EMS coordinator, City of Monroe Fire department. Kelly Wright, MS, is a City of Monroe GIS specialist.