quantitative research its characteristics strengths and weaknesses

Qualitative vs Quantitative Research Methods & Data Analysis

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What is the difference between quantitative and qualitative?

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

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

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

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

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

What Is Qualitative Research?

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

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

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

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

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

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

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

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

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

Qualitative Methods

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

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

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

Here are some examples of qualitative data:

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

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

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

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

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

Qualitative Data Analysis

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

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

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

Key Features

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

Limitations of Qualitative Research

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

Advantages of Qualitative Research

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

What Is Quantitative Research?

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

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

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

Quantitative Methods

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

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

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

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

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

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

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

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

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

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

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

Quantitative Data Analysis

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

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

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

Limitations of Quantitative Research

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

Advantages of Quantitative Research

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

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

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

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

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

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

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

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

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

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

Further Information

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

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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Quantitative method Quantitive data are pieces of information that can be counted and which are usually gathered by surveys from large numbers of respondents randomly selected for inclusion. Secondary data such as census data, government statistics, health system metrics, etc. are often included in quantitative research. Quantitative data is analysed using statistical methods. Quantitative approaches are best used to answer what, when and who questions and are not well suited to how and why questions.

Qualitative method Qualitative data are usually gathered by observation, interviews or focus groups, but may also be gathered from written documents and through case studies.  In qualitative research there is less emphasis on counting numbers of people who think or behave in certain ways and more emphasis on explaining why people think and behave in certain ways.  Participants in qualitative studies often involve smaller numbers of tools include and utilizes open-ended questionnaires interview guides.  This type of research is best used to answer how and why questions and is not well suited to generalisable what, when and who questions.

Learn more about using quantitative and qualitative approaches in various study types in the next lesson.

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Quantitative research: Definition, characteristics, benefits, limitations, and best practices

Quantitative research characteristics

Benefits and limitations, best practices for quantitative research.

Researchers use different research methods as research is carried out for various purposes. Two main forms of research, qualitative and quantitative, are widely used in different fields. While qualitative research involves using non-numeric data, quantitative research is the opposite and utilizes non-numeric data. Although quantitative research data may not offer deeper insights into the issue, it is the best practice in some instances, especially if you need to collect data from a large sample group. Quantitative research is used in various fields, including sociology, politics, psychology, healthcare, education, economics, and marketing.

Earl R. Babbie notes: "Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon."

Below are some of the characteristics of quantitative research.

Large sample size

The ability to use larger sample sizes is undoubtedly one of the biggest perks of quantitative research.

Measurability

Due to its quantitative nature, the data gathered through quantitative data collection methods is easily measurable.

Close-ended questions

Quantitative research utilizes close-ended questions, which can be both beneficial and disadvantageous.

Reusability

Since it doesn't involve open-ended questions, quantitative research results can be used in other similar research projects.

Reliability

Quantitative data is considered more reliable since it is usually free of researcher bias.

Generalization

Quantitative research uses larger sample sizes, so it is assumed that it can be generalized easily.

Since quantitative research relies on data that can be measured, there are a lot of benefits offered by quantitative methods.

Quantitative research benefits

• Easier to analyze

Analyzing numeric data is easier; in that context, quantitative research can bring large amounts of data in a short period. There is numerous quantitative data analysis software that lets the researcher analyze the data fast.

• Allows using large sample sizes

Quantitative research involves using close-ended questions or simple "yes and no" questions. Therefore, it is easier to analyze quantitative data. In that sense, it can be distributed to practically as many people as you can. A large sample size usually means more accurate research results.

• More engaging

As quantitative research questions don't feature open-ended questions, participants are more eager to respond to questions. With open-ended qualitative questions, participants sometimes need to write a wall of text, and that is undesirable for many of them. It is easier to choose "yes or no" as it doesn't require much effort. A more engaging research survey means more feedback.  

• Less biased and more accurate

Qualitative research uses open-ended questions, and since the feedback is often open to interpretation, researchers might be biased when analyzing the data. That is not the case with quantitative research, as it involves answers to preset questions. Less biased data means more accurate data.

• Needs less time and effort

In all stages of research, quantitative research requires much less time and effort when compared with qualitative research. With different software, it is possible to create, send and analyze a huge volume of quantitative data in just a few clicks. Unlike qualitative in-depth interviews that usually require participants to be in a specific office, quantitative research isn't geographically bound to any location and can be carried out online.

Quantitative research limitations

• Limited information on the subject - 

Using close-ended questions means there isn't much to interpret. It doesn't allow the researcher to get answers to "why" questions. If you want to get in-depth information on the subject, you need to carry out qualitative research.

• Can be costly

Although it allows the researcher to reach a higher sample size, finding a large number of participants is expensive, considering you have to pay each participant.

• Difficulty in confirming the feedback

Quantitative research doesn't usually involve observing participants or talking with them about their answers; therefore, it is difficult to guess if the data gathered from them is accurate all the time. With qualitative methods, you get a chance to observe participants and ask follow-up questions to confirm their answers.

What kind of research do you need?

It may sound too obvious, but you may want to think about the type of research you need to carry out before you start with one. Sometimes quantitative research is not the best practice for a given subject, and you may need to go with qualitative research.  

Clear research goals

Setting a research goal is the first thing every researcher does before setting out to carry out actual research. The success of the research hugely depends on the clearly defined research goals. In other words, it's a make or break point for most research projects. Having confusing research goals is what usually fails the entire project and results in a loss of time and money.

Use user-friendly structure

When creating your surveys and questionnaires, use a user-friendly layout and keep it simple, so it's more engaging for the users. A lot of software offers simple survey templates that you can use effectively.

Choose the right sample

Although quantitative research allows the research to use large sample sizes, it is essential to choose the right sample group. The sample group you're trying to get feedback from may not represent your target audience. Therefore, think twice before allocating resources to gathering data from them.

Pay attention to questions

Quantitative research uses closed-ended questions, which means you need to be very careful with the questions you choose. One of the benefits of quantitative research is that it gives you the ability to predetermine the questions, so you need to use this chance and think about the best possible questions you may use for a better result. With quantitative research questions, you usually don't get a chance to ask follow-up questions.

Let your bias out of the research

We already mentioned that quantitative research is less biased than qualitative research, but it doesn't mean that it's completely free of bias. In this form of research, bias comes with specifically designed questions. The researcher may frame the questions in a way that the feedback may reflect what the researcher wants. In that sense, it is important to leave all the biased questions out you feel can alter the end result of the research.

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• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

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

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

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

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

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

Table of contents

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

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

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

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

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

Quantitative data collection methods

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

Qualitative data collection methods

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

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

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

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

Quantitative research approach

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

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

Qualitative research approach

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

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

Mixed methods approach

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

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

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

Analyzing quantitative data

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

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

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

Analyzing qualitative data

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

Some common approaches to analyzing qualitative data include:

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

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

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

Research bias

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

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

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

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

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

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

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

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

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

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

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

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Strengths and Weaknesses of Quantitative and Qualitative Research

Research plays a crucial role when it comes to achieving success in the world of business. When it comes to good research, both quantitative and qualitative research matters the most in building marketing strategies. Data gained through quantitative research includes demographics, consumer growth, and market trends. All of these help businesses and marketers build new theories. Qualitative data, on the other hand, tests the existing strategies or theories based on the gathered data from open-ended sources. Organizations need both methods to run their business smoothly. Upon combining both quantitative and qualitative research, you can get more objective insights from data and achieve more impactful results.

Let’s discover more about the quantitative and qualitative research, including their strengths and weaknesses. But first let’s understand what these two types of researches are. Here we go…

What is Quantitative Research?

Quantitative research is a systematic investigation. It majorly focuses on quantifying relationships, behaviors, phenomena, or other variables by collecting and analyzing numerical data. This type of research is done to test hypotheses, measure outcomes, and determine patterns and trends. It provides theoretical analysis of statistical data, i.e. insights, calculations, and estimations. This research method significantly gathers quantifiable data to perform the systematic investigation. It employs statistical, computational, and mathematical techniques to provide accurate and reliable outcomes.

For this research study, the researcher often collects statistically authentic and valid information by conducting online surveys , questionnaires, and online polls. In addition, they use sampling methods. More often than not, this method is employed used in the fields of social sciences, economics, health, and marketing, among others to get unbiased results. It helps in drawing valid conclusions and making informed decisions to introduce transformative changes to society. Let’s now take a look at the strengths of this type of research.

Strengths of Quantitative Research

Now that you have understood what exactly quantitative research is, it’s time to look at the strengths of this research type. Here we go…

• Validity and Credibility : This type of research provide statistically valid and authentic results to help you make informed decisions.
• Objectivity and Unbiased : Data collection is structured. Therefore, researchers’ biases and preconceptions do not impact their findings.
• Broader Perspective : This allows for generalization and conclusions about a broader population. This makes the research findings more impactful and useful.
• Clear and Accurate Results : The theoretical analysis of statistical data is clear and accurate. This promotes its easy explanation to a wider audience.
• Forecast : This research study helps to forecast future trends. As a result of this, the researcher can make more informed decisions.
• Diversity : This research method allows researchers to collect quantifiable data from diverse sources such as online surveys, questionnaires, and more.
• Versatility : This is a versatile research method. It can be used in various organizations to benefit from data-driven decisions .

Let’s now take a look at the weaknesses of this type of research…

Weaknesses of Quantitative Data

Although quantitative research is versatile and its findings are very impactful, it has some weaknesses that you should know. Look at the following pointers to know the weaknesses of quantitative research:

• Alien to Real-Life Situations : Data collection is structural; however, it is often limited in nature. Since it is used to collect quantifiable data, often it is not related to real-life situations.
• Does Not Identify Causes : The objective of quantitative research is to find correlations between different variables. The researchers are concerned with how much and how many. However, they often avoid looking into the why part – why something happens.
• No New Idea : The quantitative research aims to test the hypothesis of existing concepts. It does not emphasize generating new ideas or discovering uncovered areas.
• No Subjectivity : It does not take into account human experience. There is no place for human opinions and feelings in this type of research.
• Time Consuming : It uses a larger sample size and complex data sets for analysis. Therefore, it is more time-consuming compared to the other research methods.
• Complex : The rigorous design of the study requires a high level of expertise to draw findings.

Common Types of Quantitative Research Methods

Go over the following types of quantitative research methods:

Image Source – freepik/@upklyak

Researchers often conduct surveys to gather a huge data set that can be analyzed to identify patterns, relationships, and trends. For example, you can conduct online surveys to analyze customers’ experience with products or services. This analysis helps you identify customer satisfaction levels. Furthermore, you can discover areas of improvement or change.

2. Correlation Research

This is a non-experimental method. As the name says, this method is used to discover a correlation between two variables. It does not let extraneous variables intervene in the research study. If the correlation is positive, it indicates both variables are in the same direction. On the other hand, the negative correlation suggests both variables go in a negative direction. Furthermore, this type of research method only uses existing sources to analyze the dataset. Therefore, it is considered cost-effective.

3. Causal-Comparative Research

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The casual-comparative method identifies cause and effect variables. Under this research method, one variable is dependent and another one is independent. Some researchers claim it to be similar to an experimental research method. However, this is not a complete experimental method.

4. Experimental Research

Experimental research method or true experimentation administers scientific techniques to test the hypothesis of the study. It aims to measure how independent variables impact dependent variables. Moreover, it controls extraneous variables to ensure the validity of the research design.

5. Result Analysis

Take a look at the following two methods to do the result analysis on the quantitative research:

Descriptive Analysis

This computes or calculates your datasets using mean, median, and mode to summarize the statistical dataset.

Inferential Analysis

As the name suggests, this includes inferences about what the data means. To ensure its effectiveness, researchers employ the three most common methods, including cross-tabulation, factor analysis, and T-tests.

Let’s now take a look at the important pointers you need to keep in mind when constructing surveys.

Pointers to Keep in Mind While Constructing Surveys

Check out the following pointers to know how to administer a perfect survey for quantitative research:

• The questions should be short and simple
• You should avoid asking for misleading information
• Images should be clear and legible
• Grammar and spelling mistakes can make data quality poor. So, avoid them.

Why Is Quantitative Research Important to Marketing?

Take a look at the following details to know how quantitative research is important to marketing:

Real-Time Insights

Quantitative research helps researchers gather real-time statistical data on market trends, consumer choice patterns, and the organization’s performance. Based on that, researchers compute or calculate complex datasets to gain insights into various aspects. Finally, the research insights help organizations understand the impact of their strategies. They can use this information to reform their business plans.

Improve Marketing Strategies

By gaining real-time data analytics reports on online marketing strategies , they can boost their brand visibility. This helps them determine new strategies for driving organic traffic to the website.

Competitor Analysis

Numeric data analysis helps organizations track competitors’ performance. Based on the in-depth analysis, they can compare their marketing strategies and performance with competitors. This helps them understand what they can do to increase their brand awareness.

Objectivity

The qualitative research method provides leaders with objective data. They can easily communicate this data with their team members. Furthermore, this objective data helps team members understand in which direction they should proceed to yield better results.

It’s now time to move on to another very crucial research type, i.e., Qualitative Research and understand it in detail. Here we go…

What is Qualitative Research

Qualitative research is an exploratory method. It primarily focuses on understanding human behavior, customer’s experiences, and social phenomena. It involves detailed and in-depth analysis. Unlike quantitative research, which emphasizes numerical data and statistical analysis, qualitative research strives to discover the causes of any problem by examining non-numerical data. Its main emphasis is on why rather than what. Essentially, it is subjective in nature because it typically relies on human experiences.

It employs open-ended techniques , including interviews, observations, focus groups, content analysis, and more, to collect rich data. This approach allows researchers to gain a deeper understanding of the context, motivations, and perspectives of participants. This method allows participants to express their issues and opinions in their own words. Based on the data, the researcher analyzes their attitudes, interests, behaviors, and motivations. It is often employed in the fields of education, sociology, psychology, and anthropology. The study focuses on the intricate and subtle aspects of human experiences. It often employs smaller sample sizes to facilitate an in-depth analysis of a problem. By capturing rich, detailed data, qualitative research offers a comprehensive view of the subject matter, highlighting themes, patterns, and relationships that cannot be gathered using quantitative research methods.

Strengths of Qualitative Research

Here are some of the noteworthy strengths of qualitative research that you must be aware of. Take a look…

• Data Collection : The qualitative research method is not restricted to participants’ pre-defined questions. It focuses on open-ended methods to enable data collection. Interviews/observations help a researcher gain a complete understanding of respondents. All in all, this research method focuses on collecting rich and detailed data.
• Novel Theories : This method allows researchers to generate new ideas/theories that can be opposite to conventional social beliefs and norms.
• Express in Numeric : The qualitative research method allows researchers to convert research findings into numeric data for a better understanding.
• Can combine with Quantitative Method : The researcher can combine qualitative research with quantitative research to gain incredible insights into the matter.
• Flexibility : This type of research is more flexible in nature than any other form of research, and it provides room for adaptability.
• Contextual Understanding : The researcher gains a deeper understanding of the social and cultural contexts of participants, resulting in more impactful findings.

Weaknesses of Qualitative Research

• Misleading Information : The researcher must adhere to rigorous standards when collecting and analyzing data. If they fail to do so, resources and expertise of low quality can lead to misleading results.
• Can Not Be Generalized : It is challenging to draw broad conclusions and generalize the data to a larger population using this research design.
• Time-consuming : In contrast to other research methods, the qualitative research method is time-consuming because it involves collecting data through multiple interviews and observations.
• Less Valid : Because of the human experience intervention, the qualitative research findings are believed less valid and less authentic.

Common Types of Qualitative Research Methods

Here are some common types of qualitative research methods to know:

One-on-one Interview

One-on-one interviews have emerged as one of the most popular qualitative research methods. It involves face-to-face or online interviews of the participants. This research method aims to understand and analyze the opinions, ideas, and experiences of the interviewee.

Focus Groups

This research method involves the researcher organizing a small discussion or interview with a group of participants. All of the participants need to discuss a specific topic under this method. The objective of this study is to gain an understanding of the beliefs and considerations of the participants regarding a particular topic.

Discussion Boards

Online discussion boards have replaced traditional discussion boards . Under this research method, researchers provide students with a set of questions to make them participate in the debate. This is a highly efficient way to understand their perspectives, beliefs, and ideas in different situations.

Case study is yet another kind of method used for qualitative research. This method is primarily employed to gain in-depth information about the subject. It is important to note that the subject can encompass a wide range of entities, including organizations, countries, events, or individuals. A lot of researchers view the case study method as highly explanatory.

Pictures and Videos

Pictures and videos are also used as qualitative research methods to understand human experience through image or video analysis. They enhance the richness of data by allowing participants to express themselves in a non-verbal way. Based on visual elements analysis, a researcher reveals insights into social, cultural, or psychological phenomena.

Record-Keeping or Logging

Under this research method, the researcher collects authentic and valid documents from various sources. Further, the information is used as data. The findings of this research method are considered valid and impactful.

Ethnographic Study

Under the ethnographic study, the researchers act as an active participant or observer to study participants in their natural settings. This allows them to understand their social context, culture, and behavior in a much better way.

Observation Method

The observation methods involve the researcher’s subjective interpretation to observe and analyze the attributes and characteristics of a phenomenon. The data collection relies heavily on the researcher’s keen senses of taste, smell, sight, and hearing. He conducts thorough data collection and carefully analyses the entire event.

Result Analysis

Here are the two methods that researchers often employ for the result analysis of the qualitative research:

Deductive Analysis

Deductive analysis is often used to test existing theories, ideas, or beliefs. In qualitative research, deductive analysis is the process of applying predetermined codes to the data. The codes are often generated from literature, theory, or propositions that the researcher has developed. Furthermore, this is a structured method because it applies already decided research design.

Inductive Analysis

Inductive analysis builds up new theories based on specific observations or patterns. The basis of these theories is what has been seen and how it has been seen. Furthermore, it is a flexible analysis that is open to new information.

Some people claim that surveys can only be used in quantitative research. But this is not true. You can conduct surveys in qualitative research as well to make informed decisions.

Check out the following pointers to learn what you should keep in mind while constructing surveys:

• Use appropriate language
• Avoid unnecessary capitalization in words or phrases
• Use the correct format of the questions
• Make sure that multiple-answer questions do not have conflicting answer choices.

Why Is Qualitative Research Important to Marketing?

Qualitative research is ideal for marketing because it helps organizations acquire trustworthy information regarding their consumers’ changing demands, preferences, or tastes. Go over the following pointers to understand why qualitative research is important in today’s marketing scenario. Take a look…

Build Strategies

Image Source – freepik/@storyset

In this era of cut-throat competition, knowing about your customers is crucial. This is because based on that information only you can make right marketing decisions. Qualitative research helps organizations understand customers’ preferences and needs. Information gathered using qualitative research methods help businesses build new strategies to enhance customer’s experience. Strategies that businesses design using research data help them attract their target customers and improve their bottom lines.

Rebrand Products and Services

Often, researchers find this method very helpful. The information gathered using qualitative research helps businesses rebrand their products and services. Based on the results of the research, they come to know what their products and services lack. Also, they can determine what they can do to improve their products and services to attract their target customers.

Prevents the Risk of Customer Churning

Customer churning happens when a customer stops using a company’s products or services. However, qualitative research findings help companies understand their customer’s experience with their products and know what consumers want from their products or services. This reduces the risk of customer churning to a great extent.

Get Feedback from Customers

This method helps organizations get feedback on their products or services from customers. The feedback analysis makes a lot of sense in accelerating the organization’s growth.

The Bottom Line

So, this is all about the strengths and weaknesses of quantitative and qualitative research methodologies. Both quantitative and qualitative research methods showcase unique strengths, making them ideal for collecting data for different sectors. However, both methods do exhibit some weaknesses as well. Quantitative research excels in providing precise, measurable, and generalizable data through statistical analysis, while qualitative research offers rich, detailed insights into participants’ experiences, emotions, and social interactions. Quantitative research is considered best for testing hypotheses and identifying patterns across large populations.

At the same time, qualitative research is considered ideal for gaining a deeper understanding of underlying motivations and meanings. Quantitative research methodologies have a structured approach; however, they often avoid the complexities of human behavior and context. Well, that’s not the case with qualitative research methods. You can choose to use any of the research methods to write my essay for me online based on the industry you are serving. However, you can even combine both approaches to enjoy the benefits of both methods.

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Strengths and Weaknesses of Quantitative and Qualitative Research

There are few things more useful in developing and implementing strategies than reliable data. The only drawback is that this information can be difficult to understand, which results in many business owners knowing nothing about their own research.

When starting a company or building a product, most people ask themselves the question: qualitative or quantitative research? Given the importance of coming up with a good strategy, this is not an easy question to answer.

Here is a quick look at the strengths and weaknesses of quantitative research.

What Is Quantitative Research?

Quantitative research is a study of numerical data whose purpose is to measure the strength and direction of relationships between variables. Quantitative research uses statistics to make sense of numerical data.

Quantitative research is based on numerical data gathered from different types of research methods, such as questionnaires, structured interviews, and statistical analysis.

Quantitative research involves questions that can be answered by counting or measuring, such as, how many people purchased a product? How many people are satisfied with the customer service ? What are the demographics of customers in different age groups?

For your study to be quantitative, you need to use numerical data to either prove or disprove your hypothesis.

For example, a quantitative research about a new product launch could use data like the average consumption of products in the category among the target population, the number of competitors and their individual market share, pricing points, and the marketing budget required to launch a brand awareness campaign, to mention a few.

This type of research helps you to understand your market and target audience, so you can make informed decisions about your product or service.

The biggest advantage of quantitative research is the ability to analyze large volumes of data and make conclusions based on that data.

Difference Between Qualitative And Quantitative Research

The main difference is this – Qualitative research methods include the collection of data through the use of open-ended questions, unstructured interviews, or observations, whereas, Quantitative research focuses on gathering numerical data and making generalizations about groups of people, situations, or phenomena.

Understanding human behavior and its governing reasons are the ultimate goals of Qualitative research. The discipline explores the “why” and “how” of decision-making.

Quantitative data collection methods are more structured than qualitative data collection ones.

When you need to gather a large amount of information from a group of people, there are many ways to do so. In quantitative research, data can be collected using a variety of methods, including surveys, interviews, observation, and online polls.

A good researcher knows when to use qualitative research (to understand opinions) vs quantitative research (to test objectively). 

For example, if you want to know what people think about a particular topic, then qualitative research would be best; but if you want to determine how many people are aware of a particular issue, then quantitative research would be better.

When you use both qualitative and quantitative research methods in your surveys, you will gain results that reach a lot of people as well as deeper insights from those people. With the right question types and analysis, you can use quantitative research to gain statistically significant insights into your target audience’s attitudes and behaviors.

Qualitative questions are useful for gathering detailed feedback on open-ended topics like:

Customer satisfaction. Qualitative questions let customers explain how they feel about your company’s products or services, and why they feel that way.

Employee engagement. Use open-ended questions to solicit employee feedback on company culture, management practices, benefits, and more.

Service performance. Learn why customers choose your brand over competitors’ by asking for the specific reasons for their decision.

Market research. Open-ended questions help you identify the most important factors that influence customers’ purchasing decisions in your market.

Quantitative research is ideal for:

• Collecting data at scale (e.g., using survey software)
• Reaching a large number of respondents in a short period of time
• Analyzing trends that apply to large groups of people (e.g., gender differences)
• Highlighting broad patterns or relationships between variables
• Predicting likelihoods based on certain factors (e.g., age, income)
• Driving the direction of future quantitative studies (i.e., hypothesis testing)

Importance Of Quantitative Research

The importance of quantitative research is that it provides an objective way to measure things, as well as a means of testing theories. Additionally, the results of quantitative research may be more easily replicated by other researchers.

Quantitative research is conducted in an effort to find numbers and statistical analysis to determine relationships between two or more variables. The process involves taking data from various sources and then organizing it into a format that can be used for statistical analysis.

One advantage of quantitative research is its ability to measure hard numbers and facts. This makes it much simpler to analyze data. 

For example, if you wanted to know the average income of people living in a certain area, all you would have to do is calculate the number of participants in your study who earn above and below a certain amount. You could also compare this data with other areas to see which has the highest average income levels.

Another advantage is that quantitative research allows researchers to replicate their findings using different samples or methods. The ability to replicate results ensures accuracy and consistency in results obtained from different studies conducted on similar topics over time. 

Furthermore, this type of research may reveal new insights into how something works because it focuses on measurable relationships rather than just observations about what happens in nature or human behavior itself.

Characteristics Of Quantitative Research

Quantitative research is the type of research that most people think about when they hear the word “research”. It involves creating statistical models, analyzing data, and using mathematical theories to understand how things work.

Quantitative research is used to identify factors that affect relationships between variables. Quantitative research is widely used in psychology, economics, demography, and marketing. It is often used in natural sciences, such as biology and chemistry, and in social sciences, such as sociology and psychology. Quantitative research involves the use of computational, mathematical, or statistical techniques.

For example, if a researcher believes that watching television makes people more violent, he or she may use quantitative methods to test this theory by counting the number of violent acts depicted in a week’s worth of programming and comparing it with the number of violent crimes committed for the same time period.

These are some essential characteristics of Quantitative research:

• The focus is on measurement, analysis, and prediction of phenomena through the use of mathematical models and theories.
• Quantitative research’s objective is to obtain information about the current status of a given phenomenon.
• The focus is on variables and the relationships between them.
• The researcher can manipulate variables, which is why experiments are often used in quantitative research.
• Quantitative research includes formal data collection methods.
• The results are based on large sample sizes, so the results have high statistical power and are more likely to be statistically significant (i.e., not due to chance).
• Data is analyzed using statistical techniques.
• Quantitative research typically uses deductive reasoning.
• Variables must be identified and measured using reliable instruments and procedures; using multiple methods of measurement increases the reliability and validity of results (triangulation).

The design of a quantitative research question must be structured or ‘closed’ so that it can be answered using a predetermined response format (usually dichotomous or multiple choice) or scaled responses. 

The design of the quantitative research question should not allow respondents to answer in their own words. This will make it impossible to use the data in any meaningful way. 

The quantitative design will measure whether a change has occurred from a specific point in time, but will not determine why a change has occurred.

Quantitative research questions are best for giving an overview or analysis of a particular business, industry, or topic. Therefore, they need to be researched in detail so that the researcher can be confident that enough information exists to answer the questions. If there is no literature available on the topic, then it is unlikely that you will have sufficient knowledge to investigate the topic effectively.

Conducting thorough industry research is crucial in ensuring that the quantitative research questions are well-informed and grounded in existing knowledge.

Strengths Of Quantitative Research

Quantitative research is often used to ask questions that can be answered with numerical data. It has a number of strengths:

• Standardized data collection

This means that the same instruments are used with all the participants in a study, and the data is collected in a uniform way. This makes it easier to compare results across groups of participants or to test hypotheses on a larger scale.

• Objectivity

The standardization of both data collection and analysis can make results from studies more objective than those with qualitative research methods. The use of statistics and hard numbers can also give your findings authority when you publish them online or in a print journal. This objectivity makes it easier for researchers to explain why their findings are reliable and true.

• Difficult Data Collection

Quantitative studies can also provide researchers with data about phenomena that are difficult or impossible to measure directly, such as attitudes, beliefs, and values.

Quantitative research allows for larger sample sizes, which increases the reliability of your results. It also moves quickly and can produce results that are easy to share with others, because they’re often presented as percentages.

• Generalizability

You might find that what you learn applies not only to your research participants but also to people who weren’t included in your study. For example, if you ask 1,000 people what’s important to them about their job, you might find out some things about how work affects happiness that could be true for other people as well.

• Evidence Collection

The design of a quantitative study allows the researcher to collect numerical data that can be analyzed using statistical tests. This provides an opportunity for the researcher to support or refute theories by collecting evidence that is statistically significant.

Weaknesses Of Quantitative Research

Quantitative research is a useful tool for measuring and describing the world as it exists, but it has its weaknesses as well.

Quantitative data is often criticized for being too detached from real-life situations; this criticism typically stems from the fact that the data collected tends to be structured and limited in nature. 

Some have argued that quantitative analysis does not provide people with a full picture of complex issues or human behavior since it is concerned with measuring and counting specific variables.

Quantitative researchers are concerned with how much and how many, but their methods don’t allow them to understand why something happens. They can find correlations between factors, but not necessarily causes. 

For example, they might discover that people who drink more coffee have higher rates of cardiovascular disease than people who drink less coffee, but they can’t conclude that drinking coffee causes heart problems.

Quantitative research doesn’t always take into account a human element. People make decisions based on more than just mathematical calculations, and that’s an important part of the human experience. It’s also difficult to account for the subjective nature of human experience in quantitative methods such as surveys and questionnaires.

Quantitative research tends to minimize the role of the researcher in the research process, thereby reducing the amount of information that can be obtained on contextual factors.

Quantitative research tends not to generate new ideas or shed light on unexplored areas because they focus on testing hypotheses derived from existing theories and concepts.

Types Of Quantitative Research

There are five main types of Quantitative research:

• Descriptive Research

Descriptive research produces a description of what already exists in a group or population. It usually involves taking a sample from the population in order to describe a certain characteristic of the entire group. 

It does not seek to explain why things are a certain way or how they came about but rather describes what is and what is not.

• Correlational Research

Correlational research investigates relationships between variables as well as how these variables interact with one another. 

Unlike descriptive research, correlational research goes beyond description by seeking to identify the strength, direction, and nature of relationships between two or more variables. 

While it cannot be used to determine causality due to its correlational nature, it can be used to predict outcomes based on the relationship that exists between variables.

• Experimental Research

Experimental research involves testing a hypothesis by conducting experiments using various methods such as controlled laboratory-based scenarios, field experiments, and randomized trials. 

Experimental design involves the manipulation and measurement of variables to observe their effect on each other. This enables researchers to determine cause-and-effect relationships between variables.

• Survey Research

Survey research is a quantitative method that involves the usage of different research instruments such as questionnaires or schedules to gather data. 

Surveys are usually done in cases where it is difficult to conduct an experiment such as in the case of social sciences. 

The most common forms of survey research include mail surveys, telephone interviews, and face-to-face interviews.

• Causal-Comparative Research

Causal-comparative research is a type of research that is used when the researcher has limited control over variables, such as in a field experiment. This type of research does not involve randomization of participants or experimental manipulation, as in true experimental studies.

The name causal-comparative research comes from two terms, causal and comparative. Causal implies that the study attempts to determine whether one variable causes another. Comparative indicates that groups are compared but not randomly assigned to groups by the researcher.

When To Use Quantitative Research

Quantitative research is a great way to collect data on a large scale when you have many respondents. 

This can be useful when you need a lot of data points and/or want to record responses for future analysis. It’s also good for surveys that are complex and/or have any questions. 

If your audience is large (across multiple locations, or across countries) or if you have a smaller audience but want them to complete your survey in their own language, quantitative research is the way to go.

If your business is just getting started with market research, quantitative methods will give you an excellent baseline of information upon which to build later qualitative research projects.

Qualitative research gets to the heart of your problem, giving you much more detailed data than quantitative methods would. 

Qualitative research is more appropriate for projects that:

• require more in-depth answers than “yes” or “no”
• have small sample sizes
• require detailed interviews or observations
• are exploratory in nature

Is Qualitative Or Quantitative Research Better?

A good thing to keep in mind is that there isn’t really a “right” answer – it all depends on what you are trying to find out!

Qualitative and Quantitative research is often seen as opposing approaches to research, but they both have their advantages and disadvantages. While there is a lot of debate between these two types of studies, they are not mutually exclusive and can work together to generate meaningful results.

Qualitative research gathers information that seeks to describe a topic more than measure it. Qualitative research is often used to conduct market analysis and identify consumer trends, motivations and behaviors.

Quantitative research is the best way to reveal and prove a cause-and-effect relationship. If you want to make an argument about why something is happening, quantitative research can help you do that. 

For example, if you wanted to say that more guns in the hands of private citizens lowered crime rates, you could run a study with data on crime rates and gun ownership across states and find statistical correlations between them.

Qualitative research describes and interprets what people say and do. Instead of using numbers to describe some phenomenon, it uses words and pictures instead. It’s best for exploring questions that don’t have clear answers yet, like how people feel about a new product or how they respond to a new marketing campaign.

For example, if you wanted to know how people reacted when they saw your new TV commercial, the best way would probably be to show it to people in a focus group and tape their reactions. The group moderator might ask some follow-up questions and people might comment on each other’s reactions, but the goal is less about making an argument than understanding what’s happening.

Is Survey Qualitative Or Quantitative Research?

A survey can be considered qualitative or quantitative depending on the type of questions asked. 

Quantitative surveys ask closed-ended questions – those requiring a “yes” or “no”, a number rating, or a selection from a predetermined list of answers (e.g., choose from “Excellent”, “Good”, etc.). These kinds of questions allow for analysis that can be statistically inferred across the entire population being surveyed.

Qualitative surveys (also known as unstructured interviews) ask open-ended questions that require respondents to provide free-form answers, which cannot be statistically inferred across the entire population being surveyed and therefore may not scale well if the sample size is very large.

Is Questionnaire A Quantitative Research?

A questionnaire is a series of questions or other prompts for gathering information about a subject. Although many researchers use questionnaires for statistical analysis, this is not always the case. So, yes, a questionnaire can be both, qualitative as well as quantitative, depending on the type of questions it contains.

The questionnaire is an integral part of survey research. It is a written or verbal series of questions pertaining to a specific topic, to which the respondent provides answers. 

Questionnaires are usually designed to obtain information from a large number of respondents on one or more occasions. 

The structured interview is normally used where it is necessary to keep close control over the questioning and to ensure that all respondents are asked exactly the same questions in precisely the same way.

The design process can be complex and time-consuming and many aspects need to be decided by the researcher before starting to write up the questionnaire:

• How will you distribute it? By hand? By mail? Online?
• What type of language will you use? Formal? Informal? Will it be general, or will specific jargon be included?
• How long will your questionnaire be?

Is Statistics Quantitative Research?

Quantitative research involves statistical analysis, such as calculating averages or percentages in surveys. In its most basic form, you count things, and then you make conclusions based on the numbers — usually about how common something is.

Statistics is a quantitative research method. It is used to quantify opinions, attitudes, and behaviors. This method involves the statistical analysis of data collected through polls, questionnaires, or surveys. The survey could be administered through personal interviews, telephone conversations, or the use of online survey forms.

This method is the most widely used method in business research. Most businesses make decisions based on quantitative methods. It is easy to administer with a large population size by using computers for ease of calculation and preparation of reports. It is also easy to understand and implement because it uses statistical terms that are easy to understand and interpret. This method is also used in both small and large businesses to make decisions based on quantified data.

Is Quasi-Experimental Quantitative Research?

Quasi-Experimental research is another type of experimental research design. Therefore, it is quantitative research. The difference between them is that the quasi-experimental design does not include a random sample. With this type of design, a researcher will create an experimental group and a control group, but not through random selection. Instead, the researcher will identify participants in each group based on criteria such as specific characteristics or behavior.

One advantage of Quasi-Experimental research is that it is easier to carry out than randomized experiments. It can also be less expensive because it does not require random assignment to groups. 

However, the researcher may have trouble determining whether the results from these groups are credible because there could be mitigating factors impacting the results that were not controlled for in the study’s design.

Does Quantitative Research Have Hypothesis?

Yes, quantitative research methods do have hypotheses. In fact, the whole idea of quantitative research is to test a hypothesis.

The hypothesis of quantitative research must always be stated in a clear manner. This is because the hypothesis helps to explain the relationship that exists between the different variables that have been used for the study.

However, quantitative research does not have a single hypothesis; it always has more than one hypothesis. The number and nature of these hypotheses will depend on the scope and coverage of the study or even research. The researcher will use these hypotheses to conclude whether there was any correlation between the variables that were used, or rather whether one variable had an effect on another variable.

Does Quantitative Research Use Interviews?

Interviews in quantitative research are often structured. This means that the interviewer asks the same questions, in the same order, of every respondent.

This is so that researchers are able to make comparisons between groups of people and draw conclusions about them.

For example, if a survey was looking at how many hours a week people spend on homework, it would be useful to know the subject they are studying and their level of education. These questions would be asked before asking about study time specifically so that any differences between groups can be explored further.

Respondents are also given a limited number of response options to choose from, for example, 1-5 hours 6-10 hours 11-15 hours 16-20 hours 20+ hours. 

Structured interviews also make it easier for data to be analyzed by computer programs or entered into databases.

Does Quantitative Research Focus On Human Experiences?

Quantitative research focuses on human experiences and looks into why people do certain things while others do not carry out the same actions at all. 

Quantitative research is also known as positivist research. 

It is a systematic process of collecting, organizing, analyzing, and interpreting numerical data. 

Quantitative researchers are involved in the entire research process from defining the problem to shaping the findings for presentation. 

They use probability sampling techniques, which refer to selecting samples from a population in such a way that each individual has an equal chance of being selected.

How To Determine Sample Size For Quantitative Research?

There are several methods you can use to determine the sample size. Some methods include using statistic tables and online calculators. Other methods involve using formulas to estimate sample size.

1. Using Statistic Tables

The first method you can use to calculate sample size involves using statistic tables. You need two parameters to do this; they include a confidence level and margin of error.

2. Online Calculators

The second method is by using online calculators like Survey Monkey or Raosoft Sample Size Calculator. To use these calculators, you need to fill out information such as the population, confidence interval, and margin of error among others, and click on calculate button.

3. Using Formulas

A sample size formula can be used to calculate the appropriate sample size based on factors such as population size, the margin of error, and confidence level. There are various formulas you can choose from.

Cochran’s Sample Size Formula is a common one: 

This formula can be used when one needs to determine the appropriate sample size for estimating a proportion or a percentage. 

The formula is: n = (Z 2 *p*q)/e 2 ; 

where n = sample size; p = estimated proportion; q = 1-p; e = margin of error; Z = z-score for confidence level selected. For example, 0.05 for 95% confidence interval.

Is Quantitative Research Objective?

Quantitative research focuses on measurable concepts and uses precise measurements and analysis to answer a specific question. It is thoroughly objective in nature. 

This type of research aims at testing theories by examining the relationship among variables with the help of different research tools. The relationship between variables can be causal or correlational.

In other words, quantitative researchers are more interested in determining whether the data gathered shows a true representation of the population under study.

Is Quantitative Research Scientific And Measurable?

The scientific and measurable characteristic of quantitative research is one of its greatest strengths. In fact, it’s the reason why so many scientists prefer quantitative research over qualitative research. Quantitative research can be reproduced and validated by other researchers, which makes the results generalizable and very reliable.

Because quantitative research is so reliable, it can be used to create a theory or model that accurately describes a phenomenon. 

For example, because Newton’s laws of motion have been verified by countless experiments, we can use them to develop complex models for predicting how objects will behave in different situations.

The data can be obtained using various instruments such as questionnaires and surveys. Quantitative research gathers information that is measurable, such as age, number of hours worked, and so on.

The main objective of quantitative research is to measure phenomena. It allows for the collection of numerical data that can be analyzed in order to explain what is being measured. This type of research aims at verifying theories and hypotheses by means of observation and measurements of variables.

Quantitative research does not deal with subjective ideas or opinions, but with measurable facts. It uses a deductive approach to gather information from a large sample, which then can be used to infer conclusions about the population from which it was drawn.

It can be quite useful to understand what quantitative research is, particularly when you are doing some research of your own. By understanding more about the process, you will be better prepared to make quantitative research and turn it into useful information.

Quantitative research is one of the more scientific/technical forms of market research. It’s a good way to get specific and detailed data (hence quantitative). Not only will you get statistics, numbers, etc., but you’ll actually truly learn something. It’s a great way to find out exactly what your audience wants.

Ultimately, both types of research complement one another. If you don’t have enough data yet, qualitative research can help you identify potential problems in your quantitative study. Even if you have an abundance of data from a previous research project, conducting a qualitative study prior to analyzing your quantitative data and drawing conclusions can lead to better results.

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Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

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

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of 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 employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

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

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.

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Strengths and Weaknesses of Quantitative and Qualitative Research

Insights from research, walking in your customers’ shoes.

Both qualitative and quantitative methods of user research play important roles in product development. Data from quantitative research—such as market size, demographics, and user preferences—provides important information for business decisions. Qualitative research provides valuable data for use in the design of a product—including data about user needs, behavior patterns, and use cases. Each of these approaches has strengths and weaknesses, and each can benefit from our combining them with one another. This month, we’ll take a look at these two approaches to user research and discuss how and when to apply them.

Quantitative Studies

Quantitative studies provide data that can be expressed in numbers—thus, their name. Because the data is in a numeric form, we can apply statistical tests in making statements about the data. These include descriptive statistics like the mean, median, and standard deviation, but can also include inferential statistics like t-tests, ANOVAs, or multiple regression correlations (MRC). Statistical analysis lets us derive important facts from research data, including preference trends, differences between groups, and demographics.

Multivariate statistics like the MRC or stepwise correlation regression break the data down even further and determine what factors—such as variances in preferences—we can attribute to differences between specific groups such as age groups. Quantitative studies often employ automated means of collecting data such as surveys, but we can also use other static methods—for example, examining preferences through two-alternative, forced-choice studies or examining error rates and time on task using competitive benchmarks.

Quantitative studies’ great strength is providing data that is descriptive—for example, allowing us to capture a snapshot of a user population—but we encounter difficulties when it comes to their interpretation. For example, Gallup polls commonly provide data about approval rates for the President of the United States, as shown in Figure 1, but don’t provide the crucial information that we would need to interpret that data.

In the absence of the data that would be necessary to interpret these presidential job-approval numbers, it’s difficult to say why people approve or disapprove of the job that President Obama is doing. Some respondents may feel that President Obama is too liberal, while others may feel that he is too conservative in his actions, but without the necessary data, there is no way to tell.

In a product-development environment, this data deficiency can lead to critical errors in the design of a product. For example, a survey might report that the majority of users like 3D displays, which may lead to a product team’s choosing to integrate a 3D display into their product. However, if most users like only autostereoscopic 3D displays—that is, 3D displays that don’t require their wearing glasses—or like 3D displays only for watching sports or action movies on a television, using a 3D display that requires glasses for data visualization on a mobile device might not be a sound design direction.

Basically, statistical significance tells you whether your findings are real, while effect size tells you how much they matter. For example, if you were investigating whether adding a feature would increase a product’s value, you could have a statistically significant finding, but the magnitude of the increase in value might very small—say a few cents. In contrast, a meaningful effect size might result in an increase in value of $10 per unit. Typically, if you are able to achieve statistical significance with a smaller sample size, the effect size is fairly substantial. It is important to take both statistical significance and effect size into account when interpreting your data.

Qualitative Studies

Data from qualitative studies describes the qualities or characteristics of something. You cannot easily reduce these descriptions to numbers—as you can the findings from quantitative research; though you can achieve this through an encoding process. Qualitative research studies can provide you with details about human behavior, emotion, and personality characteristics that quantitative studies cannot match. Qualitative data includes information about user behaviors, needs, desires, routines, use cases, and a variety of other information that is essential in designing a product that will actually fit into a user’s life.

While quantitative research requires the standardization of data collection to allow statistical comparison, qualitative research requires flexibility, allowing you to respond to user data as it emerges during a session. Thus, qualitative research usually takes the form of either some form of naturalistic observation such as ethnography or structured interviews. In this case, a researcher must observe and document behaviors, opinions, patterns, needs, pain points, and other types of information without yet fully understanding what data will be meaningful.

Following data collection, rather than performing a statistical analysis, researchers look for trends in the data. When it comes to identifying trends, researchers look for statements that are identical across different research participants. The rule of thumb is that hearing a statement from just one participant is an anecdote; from two, a coincidence; and hearing it from three makes it a trend. The trends that you identify can then guide product development, business decisions, and marketing strategies.

Because you cannot subject these trends to statistical analysis, you cannot validate trends by calculating a p-value or an effect size—as you could validate quantitative data—so you must employ them with care. Plus, you should continually verify such data through an ongoing qualitative research program.

Additionally, because it is not possible to automate qualitative-data collection as effectively as you can automate quantitative-data collection, it is usually extremely time consuming and expensive to gather large amounts of data, as would be typical for quantitative research studies. Therefore, it is usual to perform qualitative research with only 6 to 12 participants, while for quantitative research, it’s common for there to be hundreds or even thousands of participants. As a result, qualitative research tends to have less statistical power than quantitative research when it comes to discovering and verifying trends.

Using Quantitative and Qualitative Research Together

While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another. You can use qualitative research to identify the factors that affect the areas under investigation, then use that information to devise quantitative research that assesses how these factors would affect user preferences. To continue our earlier example regarding display preferences: if qualitative research had identified display type—such as TV, computer monitor, or mobile phone display—the researchers could have used that information to construct quantitative research that would let them determine how these variables might affect user preferences. At the same time, you can build trends that you’ve identified through quantitative research into qualitative data-collection methods and, thus verify the trends.

While this might sound contrary to what we’ve described above, the approach is actually quite straightforward. An example of a qualitative trend might be that younger users prefer autostereoscopic displays only on mobile devices, while older users prefer traditional displays on all devices. You may have discovered this by asking an open-ended, qualitative question along these lines: “What do you think of 3D displays?” This question would have opened up a discussion about 3D displays that uncovered a difference between stereoscopic displays, autostereoscopic displays, and traditional displays. In a subsequent quantitative study, you could address these factors through a series of questions such as: “Rate your level of preference for a traditional 3D display—which requires your using 3D glasses—on a mobile device,” with options ranging from strongly prefer to strongly dislike . An automated system assigns a numeric value to whatever option a participant chooses, allowing a researcher to quickly gather and analyze large amounts of data.

37 Comments

The quantitative approach is so vital, even in our daily lives, because in most, if not all things we do in life, we measure to see how much there is of something.

Quantitative method is part of our daily life, even from birth, data are constantly being collected, assessed, and re-assessed as we grow.

I also support the quantitative data because it is much used and almost whatever we do involves it.

Yes. Both quantitative and qualitative research are important on their own. It depends on the situation where a researcher conducts a particular research, or he can go for the mixed method, too. For now, I am in need of sampling and non-sampling errors. Please help me understand its applications and the ways that can be checked? Types of sampling and all related information on this chapter. Expecting someone will help me on this soon.

Quantitative data provides the facts, but facts about people are just another construct of our society. For example, is something luxurious because it’s expensive or is it expensive because it’s luxurious? Business understands that neither method should be relied upon exclusively, which is why they use both. Anyone who thinks this is a competition between the two methods to somehow win out needs to read the article again. If you want to find out what happens when you think the only tool you need to make decisions in the social world is statistics, just type ‘New Coke’ into Google.

I also think that the quantitative approach is more important than the qualitative approach because we use it more and more in our life time.

I would suggest using both quantitative and qualitative. Both are strong ways of getting information and hearing the views and suggestions of others. It would be wiser to go for a mixed research method.

This quantitative approach is the approach used to show the transparency that at the end shows the democracy in the Great lakes countries. Thanks

Both methods are useful in real life situations. Which to use depends on the situation, and it’s not bad to combine both methods as this gives better and more accurate results.

Quantitative research requires high levels of statistical understanding to enable the measurements of descriptive and inferential statistics to be computed and interpreted, whereas qualitative methods are critical to identifying gaps in underserved areas in the society. More significantly, the use of a combination of the two is perfect.

Hi, I am Mark Jonson, and I am from New York, USA. Thanks for the article and wonderful example.

I am more confused when a particular method is considered superior over the other. I am more at ease looking at all three methods as situational—in that, some decision making requires the use of a quantitative, qualitative, or mixed method to accomplish my goals. For instance, it is suitable to use the quantitative method in studying birth and death rates in Europe and Africa, whereas the qualitative method suits a study on students’ behaviour relating to a particular course of study.

I think both qualitative and quantitative are good to go by, because the demerits of one are settled by the merits of the other.

The lapses that one has are covered by the other, so I think, for better findings and more accurate results, a mixed method answers it all.

Wonderfully great to me

Good article, provides a good general overview. As a marketing-research consultant I want to stress that qualitative research helps you much more to collect insights for user stories—if you do SCRUM—get the reasons why that make you differ and not differ from competitors and that would allow you to positively stand out in the market. Quantification is great. I love the stats, measurements. Yet my clients get great stuff out of qual that quant could never deliver because it is tool for specific purposes—as qual is. If you have both in your toolbox and know how to handle them, you get a better product. Use them and use them wisely, know the strengths and weaknesses of both—or get someone who does—because your competitor might just do it right now.

Both methods play an equal role, especially in research, and may also influence each other. This will depend on time and the necessity for each method.

Both methods are relevant because they drive individuals to the same conclusions.

“On the other hand, if you achieve statistical significance with a small sample size, you don’t need to increase your sample size; the finding is true regardless.” This is not true! A significance level set to 0.05 (5%), implies that it is acceptable to have a 5% probability of incorrectly rejecting the null hypothesis. That is, one might observe statistical significance, regardless of sample size, but this may be a false positive—that is, the effect occurs by chance or due to the co-occurrence of other factors. Low statistical power—because of small sample sizes, small effects, or both—negatively affects the likelihood that a nominally statistically significant finding—that is, finding of a p-value of ~.05—actually reflects a true effect. See this example . In general, one should be cautious about making inferences based on results drawn from a small sample.

It must be remembered that the two methods are not competing. They complement each other. Employing both techniques is the surest way to get your research budget well spent.

Minini, Faith Harrison—In my opinion, all three research approaches—quantitative, qualitative, and mixed methods—are very useful in informing UX practice. However, I prefer qualitative research for the reasons that studies are cheaper to embark on and the means of data collection and analysis are less stressful. However, employing both research approaches in any given study—especially studies involving large populations in countries’ health issues—provides the best results.

Thanks for the article. Both methods are useful, but it depends on the goal of the research.

I think qualitative research is best because it involves face-to-face conversation with the respondents. It gives true and reliable data as compared to quantitative research, because those researchers obtain data only from a given source and quantify it.

I need the advantages and disadvantages of using the T-test data collection method for the United States Parcel Service about their competition. I am not sure which is better for this, t-test or not, since t-test deals in small samples whereas UPS is global. I still have to know some disadvantages and advantages though.

i think qualitative research gives you detailed information and really goes into knowing much about a phenomenon, unlike quantitative’s giving you statistics.

I think a qualitative approach is more imperative. It provides greater richness and more detailed information about a smaller number of people.

I think qualitative research is easier to make meaning from, as it simplifies the phenomena by giving details on the issues.

I beg to differ from most comments. I support qualitative research because of the quality of its results.

Good, indeed.

I now understand the concept of quantitative research. Thanks for your contribution.

This concept of quantitative research is good. Nice write-up. You can as well make a video of this and place it on Netflix for people to watch.

“While quantitative and qualitative research approaches each have their strengths and weaknesses, they can be extremely effective in combination with one another.” - very insightful and so true! Thanks for posting this post, it was, indeed, a very interesting read. However, I, personally, prefer the quantitative approach. It can provide a person with a higher quality of the result.

For the ultimate quality of both methods, a foolproof system has to be found to eliminate biases. It is almost impossible. This is the basic problem that has to be solved.

I think both qualitative and quantitative approaches are vital. The approach that the researcher will adopt should be informed by the research question that the researcher is trying to resolve.

Everyone’s story is unique. Where your story starts may not be up to you, but where it ends definitely is. Every twist and turn is an opportunity to choose what comes next. Make that choice authentically yours, and you can’t do anything but succeed. Your Rough Draft We all have a different way of finding out what will work for us. But no matter which route we take on the journey to success—however you define it—we have to get into the messy and the profound in equal measure. And once it all comes together, the structure will make sense: the who, the why, and the how.

I think both qualitative and quantitative approaches are vital. The approach that the researcher will adopt should be informed by the research question that the researcher is trying to solve.

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Strength Evolution Characteristics of Coal with Different Pore Structures and Mineral Inclusions Based on CT Scanning Reconstruction

• Original Paper
• Published: 16 August 2024

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• Cun Zhang   ORCID: orcid.org/0000-0001-8673-3077 1 , 2 ,
• Sheng Jia 1 , 2 ,
• Zhaopeng Ren 1 , 2 ,
• Qingsheng Bai 3 ,
• Lei Wang 1 , 2 &
• Penghua Han 1 , 2  

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Water–rock interactions affect mineral inclusions and the pore structure of rock, subsequently affecting its mechanical and seepage properties. A method for quantitative analysis of the pore and mineral inclusion evolution characteristics of coal samples based on CT scanning is proposed. Accordingly, numerical model construction and block division of mineral inclusions and pores in coal samples were realized. The effects of mineral inclusions and the pore structure on coal failure were simulated and analyzed. The results showed that the porosity and pore distribution in coal influence its strength. The development of plastic zones in coal affected by pores can be divided into three stages: (1) tensile failure initiation stage, (2) shear failure penetration stage, and (3) failure rapid expansion stage. The higher the fractal dimension of the pores is, the greater the strength of coal. Pores and mineral inclusions degrade the strength of coal and accelerate the development of plastic zones. In the loading process, plastic zones preferentially emerge around pores and mineral inclusions. The plastic zones around mineral inclusions connect gradually with those around pores, thus accelerating coal failure.

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Acknowledgments

Financial support for this work is provided by the National Key R&D Program of China (2023YFC3012101), the National Natural Science Foundation of China (52104155), Natural Science Foundation of Beijing Municipality (8212032), the China Postdoctoral Science Foundation (2023M733778), and the Fundamental Research Funds for the Central Universities (2024ZKPYNY01).

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Cun Zhang, Sheng Jia, Zhaopeng Ren, Lei Wang & Penghua Han

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Zhang, C., Jia, S., Ren, Z. et al. Strength Evolution Characteristics of Coal with Different Pore Structures and Mineral Inclusions Based on CT Scanning Reconstruction. Nat Resour Res (2024). https://doi.org/10.1007/s11053-024-10397-3

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