limitations of a quantitative research

Limitations and Weaknesses of Quantitative Research

Limitations and Weaknesses of Quantitative Research: Research entails the collection of materials for  academic or other purposes. It is a process of gathering information and data to solve or existing problem or prevent future problems. Research works can be done via two methods. Qualitative research or quantitative research.

Qualitative research involves the carrying out of research by gathering non-numerical data. For example, gathering of video evidence, texts or messages for analysis. On the other hand, quantitative research is the process where by numerical data are collected and analyzed. It is effectively used to find patterns and averages as well as generalising a finding or result to a wider population. Quantitative research is mostly used in natural and social sciences such as biology, psychology, economics, among others.

Quantitative research could be carried out using any four methods of researching which are descriptive research, correlational research, experimental research or survey research. In descriptive, one seeks to know the ‘what’ of a thing rather than the ‘why’ of such thing. It tries to describe the various components of an information.

Correlational research involves the research between two variables to ascertain the relationship between the variables. It understudies the impact of one variable on the other. On the other hand, an experimental research is one that uses scientific methods to establish the relationship between groups of variables. That is, it tries to establish a cause-effect relationship between the various variables under study.

Recommended: How to become a good researcher: 5 qualities you need to have.

Finally, the survey research which is most widely used involves the preparation of set questionnaires, interviews and polls to which answers are provided by a segment of the target population and then, conclusions are drawn from such answers given. Survey research studies the relationship between various variables in a given research.

One of the major benefit of  quantitative research method is that it makes one arrive at a well considered conclusion since samples are collected from those who are directly affected by the research. The data collected are majorly converted to a numerical form which aids in statistical analysis. Also, quantitative research is more convenient for projects with scientific and social science inclinations.

Also see: Advantages and Disadvantages of quantitative and qualitative Research

Weaknesses of Quantitative Research

Notwithstanding the benefits of quantitative research, the research method has its own weaknesses and limitations. This is because the method is not applicable and convenient in all cases of research. Thus, using a quantitative research method in a research where qualitative research method should be used will not produce the needed result.

To this end, some of the weaknesses and limitations of quantitative research are highlighted below.

1. It Requires a Large Number of Respondents: In the course of carrying out a quantitative research, recourse has to be made to a large number of respondents. This is because you are sampling a section of a population to get their views, which views will be seen as that of the general population. In doing this, a huge number of respondents have to be consulted so as to get a fair view or percentage of the target population.

For example, if one wishes to carry out a quantitative research in Nigeria as to her acceptance of a policy of the government, one will need to consult wider. This is because Nigeria has a population of over 200 million people and the opinions of a few thousands cannot pass out as that of 200 million people. In the light of this, more respondents will be required to be interviewed so as to enable one get a fair view of the population.

Large number of respondents is thus, one of the weaknesses or limitations of quantitative research as a small sampling of a section of the target population might not be of much help to the research.

2. It is time consuming: Unlike qualitative research which has to do with analysis of already prepared data, quantitative research demands that you source for and collate the data yourself while converting such data collected into a numerical form for proper analysis. This process is time consuming. Again, the task of sending out questionnaires to respondents and waiting for answers to such questionnaires might be time consuming as most respondents will reply late or may not even reply at all.

Great patience is therefore needed in carrying out a quantitative research. It is therefore not always a good method of research in cases of urgencies as the time to get responses might take too long.

Also see: Major characteristics of customary laws

3. It requires huge resources: Quantitative research requires huge investment of time, money and energy. It is time consuming just as it also involve huge financial commitments.

In carrying out quantitative research, one needs to get your questions prepared, sent out and also followed up to ensure that such is answered. Also, some respondents might demand to be paid before giving their inputs to such a research. An example is the trending online surveys in which the target respondents are paid for every survey they carry out for a researcher.

4. Difficulty in Analyzing the Data Collected: Data are collected from respondents and then converted into statistics. This usually poses as a limitation to a researcher who is not an expert in statistics. Analysis of collected data is also demanding and time consuming. A researcher needs to make such information collected into numerical data and correlate them with the larger population. Where this is not properly done, it means that the outcome might be false or misleading.

Also, due to the fact that a researcher might not have control over the environment he is researching in, as any such environment is susceptible to change at any point in time, the outcome of his research might be inconsistent.

Recommended: Problems and criticism of democracy

5. Outcomes of quantitative research is usually limited: In quantitative research, the outcomes are usually limited. This is because the outcome is usually based on what the researcher wants. This limited outcome is due to the structured pattern of the questionnaires. Questionnaires usually have close ended questions which gives a respondent little or no opportunity of explanations. Thus, the answers provided are limited to the questions asked and nothing more.

6. Data outcomes are usually generalised : As noted earlier, quantitative research is usually conducted on a section of a target population and not on the whole population. The outcome of this research is then generalised as the view of the entire population. What this portends is that the views of  few respondents in that research is seen as that of the general populace. Such views from them might be biased or insincere, yet they are seen as that of the entire population.

In the light of this, the fallacy of hasty generalisation is prone to be committed in a quantitative research. Generalisation of the views of a section of the population might not be the best as their views may be biased.

Recommended: Advantages and Disadvantages of Capitalism

In conclusion, quantitative research is a veritable means of conducting research especially in the fields of natural sciences and social sciences. This is because it mostly has a one on one interaction between the researcher and the various respondents as it majorly studies behavior. This advantage notwithstanding, the research method has its own  limitations and weaknesses. These limitations and weaknesses often times affect the quality of a research which is done using the quantitative method of research.

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

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)
• Click to print (Opens in new window)
• Click to email a link to a friend (Opens in new window)
• Click to share on LinkedIn (Opens in new window)
• Click to share on WhatsApp (Opens in new window)

Leave a Comment Cancel Reply

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

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

Notify me of follow-up comments by email.

Notify me of new posts by email.

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.

About Author

Send Your First Survey Today!

Set up and begin receiving results within minutes. Sign up for free, no contract required.

Helpfull is the easiest way to get feedback from thousands of people in minutes. Whether you're comparing images, text or surveys; our pool of qualified testers give you their real detailed opinion to help you make better decisions and be more informed.

Limitations and weakness of quantitative research methods

According to Saunders et al. (2009), research methodology serves as the backbone of a research study. Quantitative research’s main purpose is the quantification of the data. It allows generalisations of the results by measuring the views and responses of the sample population. Every research methodology consists of two broad phases namely planning and execution (Younus 2014). Therefore, it is evident that within these two phases, there are likely to have limitations which are beyond our control (Simon 2011). 

Improper representation of the target population

As mentioned in the article , improper representation of the target population might hinder the researcher from achieving its desired aims and objectives. Despite applying an appropriate sampling plan representation of the subjects is dependent on the probability distribution of observed data. This may lead to a miscalculation of probability distribution and lead to falsity in the proposition.

A study purports to check the proportion of females aged between 20-30 years who are applying make-up ranges of international brands. The target population, in this case, is the women belonging to the said age group, with both professional and non-professional backgrounds, residing in Delhi. The sampled population based on the probability distribution has to be calculated against the total females residing in the city (e.g. 400 sampled out of 7,800,615 female populations). However, there is a scope of getting partial information about the range of makeup products from the sampled, owing to its meagre form against the total population. Hence, the results of the study cannot be generalised in context to a larger population, but rather be suggested.

Lack of resources for data collection

Quantitative research methodology usually requires a large sample size. However, due to the lack of resources, this large-scale research becomes impossible. In many developing countries, interested parties (e.g., government or non-government organisations, public service providers, educational institutions, etc.) may lack knowledge and especially the resources needed to conduct thorough quantitative research (Science 2001).

Inability to control the environment

Sometimes researchers face problems to control the environment where the respondents provide answers to the questions in the survey (Baxter 2008). Responses often depend on a particular time which again is dependent on the conditions occurring during that particular time frame.

For example, if data for a study is collected on residents’ perception of development works conducted by the municipality, the results presented for a specific year (say, 2009), will be held redundant or of limited value in 2015. The reasons are, that either the officials have changed or the development scenario has changed (from too effective to minimal effective or vice versa).

Limited outcomes in a quantitative research

The quantitative research method involves a structured questionnaire with close-ended questions. It leads to limited outcomes outlined in the research proposal. So the results cannot always represent the actual occurrence, in a generalised form. Also, the respondents have limited options for responses, based on the selection made by the researcher.

“Does your manager motivates you to take up challenges”

The answer can be Yes / No / Can’t say or Strongly Agree to Strongly disagree. But to know what strategies are applied by the manager to motivate the employee or on what parameters the employee does not feel motivated (if responded no), the researcher has to ask broader questions which somewhat has limited scope in close-ended questionnaires

Expensive and time-consuming

Quantitative research is difficult, expensive and requires a lot of time to perform the analysis. This type of research is planned carefully in order to ensure complete randomization and correct designation of control groups (Morgan 1980). A large proportion of respondents is appropriate for the representation of the target population. So, to achieve in-depth responses on an issue, data collection in quantitative research methodology is often too expensive than the qualitative approach.

To understand the influence of advertising on the propensity of purchase decision of baby foods parents of 5-year old and below in Bangalore, the researcher needs to collect data from 200 respondents. This is time-consuming and expensive, given the approach needed for each of these parents to explain the study’s purpose.

Difficulty in data analysis

The quantitative study requires extensive statistical analysis , which can be difficult to perform for researchers from non-statistical backgrounds. Statistical analysis is based on scientific discipline and hence is difficult for non-mathematicians to perform.

Quantitative research is a lot more complex for social sciences, education, anthropology and psychology. The effective response should depend on the research problem rather than just a simple yes or no response.

To understand the level of motivation perceived by Grade 5 students from the teaching approach taken by their class teachers, mere yes and no might lead to ambiguity in data collection and hence improper results. Instead, a detailed interview or focus group technique might develop in-depth views and perspectives of both the teachers and children.

Requirement of extra resources to analyse the results

The requirements for the successful statistical confirmation of the result are very tough in quantitative research. A hypothesis is proven with few experiments due to which there is ambiguity in the results. Results are retested and refined several times for an unambiguous conclusion (Ong 2003). So it requires extra time, investment and resources to refine the results.

• Barbour, R.S., 2000. The role of qualitative research in broadening the “evidence base” for clinical practice. Journal of Evaluation in Clinical Practice , 6(2), pp.155–163.
• Baxter, P., 2008. Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers. The Qualitative Report , 13(4), pp.544–559.
• Bowen, G.A., 2006. Document Analysis as a Qualitative Research Method. Qualitative Research Journal , 9(2), pp.27 – 40.
• Elo, S. & Kyngäs, H., 2008. The qualitative content analysis process. Journal of Advanced Nursing , 62(1), pp.107–115.
• Maxwell, J.A., 2005. Qualitative Research Design: An Interactive Approach , SAGE Publications. Available at: https://books.google.co.in/books/about/Qualitative_Research_Design.html?id=XqaJP-iehskC&pgis=1 [Accessed May 20, 2015].
• Morgan, G., 1980. The Case for Qualitative Research. Academy of Management Journal , 5(4), pp.491–500.
• Ong, S.-E., 2003. Mass spectrometric-based approaches in quantitative proteomics. Methods , 29(2), pp.124–130.
• Saunders, M., Lewis, P. & Thornhill, A., 2009. Research Methods for Business Students 5th ed., Essex, England: Pearson Education Limited.
• Science, J. of D., 2001. Invited Review: Integrating Quantitative Findings from Multiple Studies Using Mixed Model Methodology. Journal of Dairy Science , 84(4), pp.741–755.
• Simon, M.K., 2011. Dissertation and scholarly research: Recipes for success , Seattle, W.A.: Dissertation Success LLC.
• Younus, M.A.F., 2014. Research Methodology. In Vulnerability and Adaptation to Climate Change in Bangladesh: Processes, Assessment and Effects (Springer Theses) . Springer, pp. 35–76. Available at: http://link.springer.com/10.1007/978-94-007-5494-2_2 [Accessed August 1, 2016].
• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)
• Click to share on LinkedIn (Opens in new window)
• Click to share on WhatsApp (Opens in new window)
• Click to share on Telegram (Opens in new window)

Notify me of follow-up comments by email.

19 thoughts on “Limitations and weakness of quantitative research methods”

Proofreading.

Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

What is the difference between quantitative and qualitative?

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

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

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

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

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

What Is Qualitative Research?

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

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

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

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

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

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

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

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

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

Qualitative Methods

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

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

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

Here are some examples of qualitative data:

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

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

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

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

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

Qualitative Data Analysis

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

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

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

Key Features

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

Limitations of Qualitative Research

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

Advantages of Qualitative Research

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

What Is Quantitative Research?

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

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

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

Quantitative Methods

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

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

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

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

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

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

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

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

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

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

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

Quantitative Data Analysis

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

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

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

Limitations of Quantitative Research

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

Advantages of Quantitative Research

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

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

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

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

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

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

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

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

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

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

Further Information

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

Have a language expert improve your writing

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

• Knowledge Base

Methodology

• 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.

Cite this Scribbr article

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

Streefkerk, R. (2023, June 22). Qualitative vs. Quantitative Research | Differences, Examples & Methods. Scribbr. Retrieved March 29, 2024, from https://www.scribbr.com/methodology/qualitative-quantitative-research/

Is this article helpful?

Raimo Streefkerk

Other students also liked, what is quantitative research | definition, uses & methods, what is qualitative research | methods & examples, mixed methods research | definition, guide & examples, unlimited academic ai-proofreading.

✔ Document error-free in 5minutes ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

Handbook of Research Methods in Health Social Sciences pp 27–49 Cite as

Quantitative Research

• Leigh A. Wilson 2 , 3  
• Reference work entry
• First Online: 13 January 2019

4027 Accesses

4 Citations

Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.

• Quantitative
• Epidemiology
• Data analysis
• Methodology
• Interpretation

This is a preview of subscription content, log in via an institution .

Buying options

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Babbie ER. The practice of social research. 14th ed. Belmont: Wadsworth Cengage; 2016.

Google Scholar  

Descartes. Cited in Halverston, W. (1976). In: A concise introduction to philosophy, 3rd ed. New York: Random House; 1637.

Doll R, Hill AB. The mortality of doctors in relation to their smoking habits. BMJ. 1954;328(7455):1529–33. https://doi.org/10.1136/bmj.328.7455.1529 .

Article   Google Scholar  

Liamputtong P. Research methods in health: foundations for evidence-based practice. 3rd ed. Melbourne: Oxford University Press; 2017.

McNabb DE. Research methods in public administration and nonprofit management: quantitative and qualitative approaches. 2nd ed. New York: Armonk; 2007.

Merriam-Webster. Dictionary. http://www.merriam-webster.com . Accessed 20th December 2017.

Olesen Larsen P, von Ins M. The rate of growth in scientific publication and the decline in coverage provided by Science Citation Index. Scientometrics. 2010;84(3):575–603.

Pannucci CJ, Wilkins EG. Identifying and avoiding bias in research. Plast Reconstr Surg. 2010;126(2):619–25. https://doi.org/10.1097/PRS.0b013e3181de24bc .

Petrie A, Sabin C. Medical statistics at a glance. 2nd ed. London: Blackwell Publishing; 2005.

Portney LG, Watkins MP. Foundations of clinical research: applications to practice. 3rd ed. New Jersey: Pearson Publishing; 2009.

Sheehan J. Aspects of research methodology. Nurse Educ Today. 1986;6:193–203.

Wilson LA, Black DA. Health, science research and research methods. Sydney: McGraw Hill; 2013.

Download references

Author information

Authors and affiliations.

School of Science and Health, Western Sydney University, Penrith, NSW, Australia

Leigh A. Wilson

Faculty of Health Science, Discipline of Behavioural and Social Sciences in Health, University of Sydney, Lidcombe, NSW, Australia

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Leigh A. Wilson .

Editor information

Editors and affiliations.

Pranee Liamputtong

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this entry

Cite this entry.

Wilson, L.A. (2019). Quantitative Research. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_54

Download citation

DOI : https://doi.org/10.1007/978-981-10-5251-4_54

Published : 13 January 2019

Publisher Name : Springer, Singapore

Print ISBN : 978-981-10-5250-7

Online ISBN : 978-981-10-5251-4

eBook Packages : Social Sciences Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

Share this entry

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

13 Pros and Cons of Quantitative Research Methods

Quantitative research utilizes mathematical, statistical, and computational tools to derive results. This structure creates a conclusiveness to the purposes being studied as it quantifies problems to understand how prevalent they are.

It is through this process that the research creates a projectable result which applies to the larger general population.

Instead of providing a subjective overview like qualitative research offers, quantitative research identifies structured cause-and-effect relationships. Once the problem is identified by those involved in the study, the factors associated with the issue become possible to identify as well. Experiments and surveys are the primary tools of this research method to create specific results, even when independent or interdependent factors are present.

These are the quantitative research pros and cons to consider.

List of the Pros of Quantitative Research

1. Data collection occurs rapidly with quantitative research. Because the data points of quantitative research involve surveys, experiments, and real-time gathering, there are few delays in the collection of materials to examine. That means the information under study can be analyzed very quickly when compared to other research methods. The need to separate systems or identify variables is not as prevalent with this option either.

2. The samples of quantitative research are randomized. Quantitative research uses a randomized process to collect information, preventing bias from entering into the data. This randomness creates an additional advantage in the fact that the information supplied through this research can then be statistically applied to the rest of the population group which is under study. Although there is the possibility that some demographics could be left out despite randomization to create errors when the research is applied to all, the results of this research type make it possible to glean relevant data in a fraction of the time that other methods require.

3. It offers reliable and repeatable information. Quantitative research validates itself by offering consistent results when the same data points are examined under randomized conditions. Although you may receive different percentages or slight variances in other results, repetitive information creates the foundation for certainty in future planning processes. Businesses can tailor their messages or programs based on these results to meet specific needs in their community. The statistics become a reliable resource which offer confidence to the decision-making process.

4. You can generalize your findings with quantitative research. The issue with other research types is that there is no generalization effect possible with the data points they gather. Quantitative information may offer an overview instead of specificity when looking at target groups, but that also makes it possible to identify core subjects, needs, or wants. Every finding developed through this method can go beyond the participant group to the overall demographic being looked at with this work. That makes it possible to identify trouble areas before difficulties have a chance to start.

5. The research is anonymous. Researchers often use quantitative data when looking at sensitive topics because of the anonymity involved. People are not required to identify themselves with specificity in the data collected. Even if surveys or interviews are distributed to each individual, their personal information does not make it to the form. This setup reduces the risk of false results because some research participants are ashamed or disturbed about the subject discussions which involve them.

6. You can perform the research remotely. Quantitative research does not require the participants to report to a specific location to collect the data. You can speak with individuals on the phone, conduct surveys online, or use other remote methods that allow for information to move from one party to the other. Although the number of questions you ask or their difficulty can influence how many people choose to participate, the only real cost factor to the participants involves their time. That can make this option a lot cheaper than other methods.

7. Information from a larger sample is used with quantitative research. Qualitative research must use small sample sizes because it requires in-depth data points to be collected by the researchers. This creates a time-consuming resource, reducing the number of people involved. The structure of quantitative research allows for broader studies to take place, which enables better accuracy when attempting to create generalizations about the subject matter involved. There are fewer variables which can skew the results too because you’re dealing with close-ended information instead of open-ended questions.

List of the Cons of Quantitative Research

1. You cannot follow-up on any answers in quantitative research. Quantitative research offers an important limit: you cannot go back to participants after they’ve filled out a survey if there are more questions to ask. There is a limited chance to probe the answers offered in the research, which creates fewer data points to examine when compared to other methods. There is still the advantage of anonymity, but if a survey offers inconclusive or questionable results, there is no way to verify the validity of the data. If enough participants turn in similar answers, it could skew the data in a way that does not apply to the general population.

2. The characteristics of the participants may not apply to the general population. There is always a risk that the research collected using the quantitative method may not apply to the general population. It is easy to draw false correlations because the information seems to come from random sources. Despite the efforts to prevent bias, the characteristics of any randomized sample are not guaranteed to apply to everyone. That means the only certainty offered using this method is that the data applies to those who choose to participate.

3. You cannot determine if answers are true or not. Researchers using the quantitative method must operate on the assumption that all the answers provided to them through surveys, testing, and experimentation are based on a foundation of truth. There are no face-to-face contacts with this method, which means interviewers or researchers are unable to gauge the truthfulness or authenticity of each result.

A 2011 study published by Psychology Today looked at how often people lie in their daily lives. Participants were asked to talk about the number of lies they told in the past 24 hours. 40% of the sample group reported telling a lie, with the median being 1.65 lies told per day. Over 22% of the lies were told by just 1% of the sample. What would happen if the random sampling came from this 1% group?

4. There is a cost factor to consider with quantitative research. All research involves cost. There’s no getting around this fact. When looking at the price of experiments and research within the quantitative method, a single result mist cost more than $100,000. Even conducting a focus group is costly, with just four groups of government or business participants requiring up to $60,000 for the work to be done. Most of the cost involves the target audiences you want to survey, what the objects happen to be, and if you can do the work online or over the phone.

5. You do not gain access to specific feedback details. Let’s say that you wanted to conduct quantitative research on a new toothpaste that you want to take to the market. This method allows you to explore a specific hypothesis (i.e., this toothpaste does a better job of cleaning teeth than this other product). You can use the statistics to create generalizations (i.e., 70% of people say this toothpaste cleans better, which means that is your potential customer base). What you don’t receive are specific feedback details that can help you refine the product. If no one likes the toothpaste because it tastes like how a skunk smells, that 70% who say it cleans better still won’t purchase the product.

6. It creates the potential for an unnatural environment. When carrying out quantitative research, the efforts are sometimes carried out in environments which are unnatural to the group. When this disadvantage occurs, the results will often differ when compared to what would be discovered with real-world examples. That means researchers can still manipulate the results, even with randomized participants, because of the work within an environment which is conducive to the answers which they want to receive through this method.

These quantitative research pros and cons take a look at the value of the information collected vs. its authenticity and cost to collect. It is cheaper than other research methods, but with its limitations, this option is not always the best choice to make when looking for specific data points before making a critical decision.

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Quantitative Methods
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

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.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Need Help Locating Statistics?

Resources for locating data and statistics can be found here:

Statistics & Data Research Guide

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

• Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
• Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
• Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
• You can summarize vast sources of information and make comparisons across categories and over time; and,
• Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

• Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
• Uses a static and rigid approach and so employs an inflexible process of discovery;
• The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
• Results provide less detail on behavior, attitudes, and motivation;
• Researcher may collect a much narrower and sometimes superficial dataset;
• Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
• The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
• Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

• << Previous: Qualitative Methods
• Next: Insiderness >>
• Last Updated: Mar 26, 2024 10:40 AM
• URL: https://libguides.usc.edu/writingguide

Advantages and Disadvantages of Quantitative Research

• Market Research
• Sustainable Businesses
• Supply Chain Management
• Operations & Technology
• Business Law & Taxes
• Business Insurance
• Business Finance
• Becoming an Owner
• University of Washington
• San Jose State University
• University of California, San Diego

Quantitative research is the process of gathering observable data to answer a research question using statistical , computational, or mathematical techniques. It is often seen as more accurate or valuable than qualitative research, which focuses on gathering non-numerical data.

Qualitative research looks at opinions, concepts, characteristics, and descriptions. Quantitative research looks at measurable, numerical relationships. Both kinds of research have their advantages and disadvantages .

How Can Businesses Use Quantitative Research?

Research benefits small businesses by helping you make informed decisions. Conducting market research should be a regular part of any business plan, allowing you to grow efficiently and make good use of your available resources.

Businesses can use research to:

• Learn more about customer opinions and buying patterns .
• Test new products and services before launching them.
• Make decisions about product packaging, branding, and other visual elements.
• Understand patterns in your market or industry.
• Analyze the behavior of your competitors.
• Identify the best use of your marketing resources.
• Compare how successful different promotions will be before scaling up.
• Decide on where new locations or stores should be.

When deciding what type of research will benefit your business, it is important to consider the advantages and disadvantages of quantitative research.

Advantages of Quantitative Research

The use of statistical analysis and hard numbers found in quantitative research has distinct advantages in the research process.

• Can be tested and checked. Quantitative research requires careful experimental design and the ability for anyone to replicate both the test and the results. This makes the data you gather more reliable and less open to argument.
• Straightforward analysis. When you collect quantitative data, the type of results will tell you which statistical tests are appropriate to use. As a result, interpreting your data and presenting those findings is straightforward and less open to error and subjectivity.
• Prestige. Research that involves complex statistics and data analysis is considered valuable and impressive because many people don't understand the mathematics involved. Quantitative research is associated with technical advancements like computer modeling, stock selection, portfolio evaluation, and other data-based business decisions. The association of prestige and value with quantitative research can reflect well on your small business.

Disadvantages of Quantitative Research

However, the focus on numbers found in quantitative research can also be limiting, leading to several disadvantages.

• False focus on numbers. Quantitative research can be limited in its pursuit of concrete, statistical relationships, which can lead to researchers overlooking broader themes and relationships. By focusing solely on numbers, you run the risk of missing surprising or big-picture information that can benefit your business.
• Difficulty setting up a research model. When you conduct quantitative research, you need to carefully develop a hypothesis and set up a model for collecting and analyzing data. Any errors in your set up, bias on the part of the researcher, or mistakes in execution can invalidate all your results. Even coming up with a hypothesis can be subjective, especially if you have a specific question that you already know you want to prove or disprove.
• Can be misleading. Many people assume that because quantitative research is based on statistics it is more credible or scientific than observational, qualitative research. However, both kinds of research can be subjective and misleading. The opinions and biases of a researcher are just as likely to impact quantitative approaches to information gathering. In fact, the impact of this bias occurs earlier in the process of quantitative research than it does in qualitative research.

Tips for Conducting Quantitative Research

If you decide to conduct quantitative research for your small business,

• Work with a professional. Professional market researchers and data analysts are trained in how to conduct survey research and run statistical models. To ensure that your research is well-designed and your results are accurate, work with a professional. If you can't afford to hire researchers for the length of the project, look for someone who can help just with set-up or analysis.
• Have a clear research question. To save time and resources, have a clear idea of what question you want answered before you begin researching. You can find areas that need research by looking at your marketing plan and identifying where you struggle to make an informed decision.
• Don't be afraid to change your model. Research is a process, and needing to change direction or start over doesn't mean you have failed or done something wrong. Often, successful research will raise new questions. Keep track of those new questions so that you can continue answering them as you move forward.
• Combine quantitative and qualitative research. Successfully running a small business relies on understanding people, and the behavior of your customers and competitors cannot be reduced to numbers. As you conduct quantitative research, try to collect qualitative data as well. This can take the form of open-ended questions on surveys, panel discussions, or even just keeping track of opinions or concerns that customers share. By combining the two types of research, you'll end up with the best possible picture of how your business can grow and succeed within its market.
• Deductive and Inductive Market Research
• Qualitative and Quantitative Research Methods
• Establishing Trustworthiness in Qualitative Research
• Market Research 101: Develop the Research Plan
• Surveys Research: Confidence Intervals and Levels
• What Is Market Research?
• How to Conduct Market Research Surveys
• Starting Market Research: Identify Your Marketing Research Problem
• Developing the Overall Research Plan
• Qualitative or Quantitative? How to Choose a Method for Your Survey
• How to Analyze Interview Data and Survey Responses
• How to Use a Codebook for Qualitative Research Analysis
• How to Analyze Small Business Qualitative Market Research
• How the SBA Can Help Your Small Business
• How to Conduct a Delphi Survey
• Best Jobs for Graduates With a Mathematics Degree

Ask Jordon’s Newsletter

Exploring the benefits and limitations of quantitative research methods in higher, education and sciences: a comprehensive overview.

Introduction:

Quantitative research methods are often favoured for gathering and analysing data in higher education research because of their replicability in their experimental design. Research design is a crucial aspect of conducting research, and three commonly used designs in the quantitative analysis are experimental, quasi-experimental, and non-experimental. These Sampling and data collection are also essential steps in the research process, with probability and non-probability sampling methods and surveys/questionnaires, observation, experimentation, and secondary data analysis being commonly used data collection methods. Data analysis methods include descriptive statistics, inferential statistics, and regression analysis, which help researchers draw conclusions about their research question. This blog article will examine how to explore quantitative studies through my experiences conducting this biology and social sciences research. It will also explore the advantages and disadvantages of the various methods and approaches, discussing the scope and limitations. Quantitative research methods are valuable tools for researchers to understand various phenomena.

Exploring the Three Main Research Designs in Quantitative Analysis

In previous articles, I have outlined how research design is crucial to your project or dissertation. Three research designs are typically used in quantitative analysis: experimental, quasi-experimental, and non-experimental.

Experimental Design:

Experimental design involves manipulating one or more independent variables to observe the effect on the dependent variable. This design is helpful in higher education research to test the effectiveness of a new teaching method or instructional technology, for example, comparing the learning outcomes of traditional lectures versus online learning environments.

Quasi-experimental Design:

A quasi-experimental design is similar to an experimental procedure, but the researcher cannot randomly assign participants to groups. Instead, pre-existing groups are used for comparison purposes. This could be used by looking at flock performances on chicken or turkey growth rates based on an additive introduced to shed rations. Due to flocks having an inherently limited time through the production cycle, a measure of looking at different crops would be the only way to assess productivity changes.

Non-experimental Design:

The non-experimental design does not involve the manipulation of independent variables. Instead, it consists of the observation of naturally occurring phenomena. Often this method may be explored in behavioural research using ethograms and time budgets to measure groups or individual animal responses. This design can be used in higher education research to explore the relationship between a student's socioeconomic class and academic performance.

Sampling: The Art and Science of Participant Selection in Quantitative Research

Sampling refers to the process of selecting participants for a research study. There are two types of sampling methods: probability sampling and non-probability sampling. Probability sampling involves randomly selecting participants from a population, ensuring each member has an equal chance of being selected. Non-probability selection involves selecting participants based on specific criteria, which is useful when the population is too large to choose a random sample or when the research question requires a particular type of participant.

The process of selecting participants for a research project is called sampling. Probability sampling and non-probability sampling are the two types of sampling procedures. Probability sampling entails randomly picking members from a population, guaranteeing that each member has an equal probability of being chosen. Non-probability selection is selecting participants based on specific criteria, which is advantageous when the population is too big to pick a random sample or when the research question necessitates a particular sort of participant.

Unleashing the Full Potential of Data Collection Methods in Quantitative Research

The process of acquiring information for a research study is known as data collection. Surveys/questionnaires, observation, experimentation, and secondary data analysis are quantitative research's four standard data-gathering methods. Surveys/questionnaires entail asking participants to answer standard questions, whereas statements entail monitoring and documenting behaviour. The investigation involves modifying one or more independent factors to maintain the effect on the dependent variable, whereas secondary data analysis is analysing previously acquired data for a new reason.

Both the social and biological sciences benefit from quantitative research methodologies. Quantitative research methods can be used to investigate social phenomena and behaviour in the social sciences, such as political science, sociology, psychology, and economics. Quantitative research methods can be used to examine living creatures and their environments in biological disciplines such as agriculture, medicine, and animal studies.

From Agriculture to Politics: The Versatility of Quantitative Research Methods in Social and Biological Sciences

Quantitative research methods are widely used in many social and biological sciences areas. These strategies entail gathering and analysing numerical data to comprehend patterns and relationships. This blog article will examine concrete examples of how quantitative research methods are employed in many sectors and their benefits and drawbacks.

In political science, quantitative research methods are used to analyse political behaviour, public opinion, and voting trends. If you were studying ecology policy and wanted to gauge the public's reception to your project's proposal, such as their view on swift boxes in domestic properties proposals, a measure that has been explored in Brighton and successfully to benefit a population. Outputs such as the demographic of individuals and understanding their levels of responses to the question.

Researchers utilise surveys and experiments to better understand how individuals make political decisions and how government policies influence society. Sociologists use surveys and experiments to explore inequality, social mobility, and social change. In psychology, quantitative research methods investigate human behaviour and mental processes such as personality, emotion, and cognitive functions. Economic researchers use statistical analysis to analyse consumer behaviour, labour markets, and economic growth. Quantitative research methods are also applied in the biological sciences. Researchers employ experiments and statistical analysis to create new farming practices and boost agricultural sustainability. Whether this is in understanding new production techniques such as vertical farming using grey water, which can be examined to assess the viability of crop production against traditional measures.

Pros and Cons: Understanding the Advantages and Limitations of Quantitative Research Methods

Quantitative research methods offer various advantages, including exact variable measurement, which can lead to more accurate and dependable conclusions. These procedures are straightforward to replicate, which adds to the findings' validity. Moreover, statistical analysis enables the detection of patterns and correlations in data. Yet, quantitative research approaches have several disadvantages. They may need to be adapted for measuring or quantifying complex objects. These approaches may also limit their ability to capture the depth and complexity of human experience, and they may be prone to biases and assumptions that weaken the validity of the findings.

Conclusion:

In conclusion, quantitative research methods are valuable tools for researchers to gather and analyse data to draw conclusions about various phenomena. The research design, sampling, data collection, and data analysis are essential steps in the research process, with experimental, quasi-experimental, and non-experimental techniques commonly used in quantitative analysis. Probability and non-probability sampling methods and surveys/questionnaires, observation, experimentation, and secondary data analysis are widely used data collection methods. Descriptive statistics, inferential statistics, and regression analysis are standard data analysis methods used to draw conclusions about the research question. Quantitative research methods have advantages and disadvantages and are widely used in various fields, including social and biological sciences, to study phenomena and behaviour and develop new techniques and interventions. Despite the limitations, the precise measurement of variables, replicability, and ability to identify patterns and relationships in the data make quantitative research methods a valuable tool for researchers.

Ready for more?

An official website of the United States government

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

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

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Korean Med Sci
• v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

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

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

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

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

• Privacy Policy

Buy Me a Coffee

Home » Limitations in Research – Types, Examples and Writing Guide

Limitations in Research – Types, Examples and Writing Guide

Table of Contents

Limitations in Research

Limitations in research refer to the factors that may affect the results, conclusions , and generalizability of a study. These limitations can arise from various sources, such as the design of the study, the sampling methods used, the measurement tools employed, and the limitations of the data analysis techniques.

Types of Limitations in Research

Types of Limitations in Research are as follows:

Sample Size Limitations

This refers to the size of the group of people or subjects that are being studied. If the sample size is too small, then the results may not be representative of the population being studied. This can lead to a lack of generalizability of the results.

Time Limitations

Time limitations can be a constraint on the research process . This could mean that the study is unable to be conducted for a long enough period of time to observe the long-term effects of an intervention, or to collect enough data to draw accurate conclusions.

Selection Bias

This refers to a type of bias that can occur when the selection of participants in a study is not random. This can lead to a biased sample that is not representative of the population being studied.

Confounding Variables

Confounding variables are factors that can influence the outcome of a study, but are not being measured or controlled for. These can lead to inaccurate conclusions or a lack of clarity in the results.

Measurement Error

This refers to inaccuracies in the measurement of variables, such as using a faulty instrument or scale. This can lead to inaccurate results or a lack of validity in the study.

Ethical Limitations

Ethical limitations refer to the ethical constraints placed on research studies. For example, certain studies may not be allowed to be conducted due to ethical concerns, such as studies that involve harm to participants.

Examples of Limitations in Research

Some Examples of Limitations in Research are as follows:

Research Title: “The Effectiveness of Machine Learning Algorithms in Predicting Customer Behavior”

Limitations:

• The study only considered a limited number of machine learning algorithms and did not explore the effectiveness of other algorithms.
• The study used a specific dataset, which may not be representative of all customer behaviors or demographics.
• The study did not consider the potential ethical implications of using machine learning algorithms in predicting customer behavior.

Research Title: “The Impact of Online Learning on Student Performance in Computer Science Courses”

• The study was conducted during the COVID-19 pandemic, which may have affected the results due to the unique circumstances of remote learning.
• The study only included students from a single university, which may limit the generalizability of the findings to other institutions.
• The study did not consider the impact of individual differences, such as prior knowledge or motivation, on student performance in online learning environments.

Research Title: “The Effect of Gamification on User Engagement in Mobile Health Applications”

• The study only tested a specific gamification strategy and did not explore the effectiveness of other gamification techniques.
• The study relied on self-reported measures of user engagement, which may be subject to social desirability bias or measurement errors.
• The study only included a specific demographic group (e.g., young adults) and may not be generalizable to other populations with different preferences or needs.

How to Write Limitations in Research

When writing about the limitations of a research study, it is important to be honest and clear about the potential weaknesses of your work. Here are some tips for writing about limitations in research:

• Identify the limitations: Start by identifying the potential limitations of your research. These may include sample size, selection bias, measurement error, or other issues that could affect the validity and reliability of your findings.
• Be honest and objective: When describing the limitations of your research, be honest and objective. Do not try to minimize or downplay the limitations, but also do not exaggerate them. Be clear and concise in your description of the limitations.
• Provide context: It is important to provide context for the limitations of your research. For example, if your sample size was small, explain why this was the case and how it may have affected your results. Providing context can help readers understand the limitations in a broader context.
• Discuss implications : Discuss the implications of the limitations for your research findings. For example, if there was a selection bias in your sample, explain how this may have affected the generalizability of your findings. This can help readers understand the limitations in terms of their impact on the overall validity of your research.
• Provide suggestions for future research : Finally, provide suggestions for future research that can address the limitations of your study. This can help readers understand how your research fits into the broader field and can provide a roadmap for future studies.

Purpose of Limitations in Research

There are several purposes of limitations in research. Here are some of the most important ones:

• To acknowledge the boundaries of the study : Limitations help to define the scope of the research project and set realistic expectations for the findings. They can help to clarify what the study is not intended to address.
• To identify potential sources of bias: Limitations can help researchers identify potential sources of bias in their research design, data collection, or analysis. This can help to improve the validity and reliability of the findings.
• To provide opportunities for future research: Limitations can highlight areas for future research and suggest avenues for further exploration. This can help to advance knowledge in a particular field.
• To demonstrate transparency and accountability: By acknowledging the limitations of their research, researchers can demonstrate transparency and accountability to their readers, peers, and funders. This can help to build trust and credibility in the research community.
• To encourage critical thinking: Limitations can encourage readers to critically evaluate the study’s findings and consider alternative explanations or interpretations. This can help to promote a more nuanced and sophisticated understanding of the topic under investigation.

When to Write Limitations in Research

Limitations should be included in research when they help to provide a more complete understanding of the study’s results and implications. A limitation is any factor that could potentially impact the accuracy, reliability, or generalizability of the study’s findings.

It is important to identify and discuss limitations in research because doing so helps to ensure that the results are interpreted appropriately and that any conclusions drawn are supported by the available evidence. Limitations can also suggest areas for future research, highlight potential biases or confounding factors that may have affected the results, and provide context for the study’s findings.

Generally, limitations should be discussed in the conclusion section of a research paper or thesis, although they may also be mentioned in other sections, such as the introduction or methods. The specific limitations that are discussed will depend on the nature of the study, the research question being investigated, and the data that was collected.

Examples of limitations that might be discussed in research include sample size limitations, data collection methods, the validity and reliability of measures used, and potential biases or confounding factors that could have affected the results. It is important to note that limitations should not be used as a justification for poor research design or methodology, but rather as a way to enhance the understanding and interpretation of the study’s findings.

Importance of Limitations in Research

Here are some reasons why limitations are important in research:

• Enhances the credibility of research: Limitations highlight the potential weaknesses and threats to validity, which helps readers to understand the scope and boundaries of the study. This improves the credibility of research by acknowledging its limitations and providing a clear picture of what can and cannot be concluded from the study.
• Facilitates replication: By highlighting the limitations, researchers can provide detailed information about the study’s methodology, data collection, and analysis. This information helps other researchers to replicate the study and test the validity of the findings, which enhances the reliability of research.
• Guides future research : Limitations provide insights into areas for future research by identifying gaps or areas that require further investigation. This can help researchers to design more comprehensive and effective studies that build on existing knowledge.
• Provides a balanced view: Limitations help to provide a balanced view of the research by highlighting both strengths and weaknesses. This ensures that readers have a clear understanding of the study’s limitations and can make informed decisions about the generalizability and applicability of the findings.

Advantages of Limitations in Research

Here are some potential advantages of limitations in research:

• Focus : Limitations can help researchers focus their study on a specific area or population, which can make the research more relevant and useful.
• Realism : Limitations can make a study more realistic by reflecting the practical constraints and challenges of conducting research in the real world.
• Innovation : Limitations can spur researchers to be more innovative and creative in their research design and methodology, as they search for ways to work around the limitations.
• Rigor : Limitations can actually increase the rigor and credibility of a study, as researchers are forced to carefully consider the potential sources of bias and error, and address them to the best of their abilities.
• Generalizability : Limitations can actually improve the generalizability of a study by ensuring that it is not overly focused on a specific sample or situation, and that the results can be applied more broadly.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

How to Cite Research Paper – All Formats and...

Data Collection – Methods Types and Examples

Delimitations in Research – Types, Examples and...

Research Paper Format – Types, Examples and...

Research Process – Steps, Examples and Tips

Research Design – Types, Methods and Examples

How to use qualitative and quantitative research to your advantage

• Share on Facebook
• Share on Twitter
• Share on LinkedIn

Qualitative research and quantitative research are market research methods that are widely used by market research companies and consumer research platforms . They act as powerful sources of insight for marketers, storytellers, journalists, psychologists, economists, brand managers, social scientists – the list goes on.

What is quantitative research?

Quantitative research is a numbers thing. It gives you an idea of how many people think, feel, or behave in a certain way. You tend to be dealing with a large sample here – one that more accurately represents a wider group.

Quantitative research calls on surveys or analytics to quantify consumer behaviors, perceptions, attitudes, and interests, giving you the hard numbers you need to back your ideas .

Here’s an example: Logging into TikTok every day has increased by 54% outside China since the end of 2020.

What is qualitative research?

Generally speaking, qualitative research explores what people think, feel, and do. It’s non-numerical, which means your insights will consist of words and stories, like people talking about their experiences and sharing their opinions. 

You tend to be dealing with a small sample here. Qualitative research is usually gathered from sources such as one-on-one interviews, focus groups, and discussion forums.

This is great for generating first-hand insight, like uncovering a customer’s perception of your value proposition, or how their attitudes are changing.

Here’s an example: Consumers feel that treating themselves and indulging has become more important.

If quantitative research is the outline of a picture, qualitative research colors it in.

Qualitative research vs. quantitative research: how do they fare?

Both research methods have pros and cons, and depending on what type of data you’re after, one will be better suited.

The benefits of qualitative research

• Get depth and detail: A qualitative research method helps you analyze thoughts, feelings, and behaviors. In doing so, it lets you explore the ‘why’ behind things. This is immensely valuable when it comes to understanding what motivates consumers – and in turn, what drives their behavior.
• You can encourage discussion: The joy of qualitative data is that it allows people to expand on the ins and outs of how they’re feeling. Often, these discussions can introduce new topic areas you didn’t originally think of, providing deeper insight.
• You can stay flexible: On the back of the above point, using a qualitative method lets you adapt your questions in real-time, depending on the information you’re gathering. If you’ve scratched the surface of something interesting, you can dig a little deeper. And if it’s not hitting the mark, you can shift the focus of the question.

The drawbacks of qualitative research

• You’re dealing with small sample sizes: Qualitative analysis tends to be more in-depth, which is great, but it’s more time-consuming as a result. And because it’s resource-intensive, the number of people you can actually speak to is limited. Chances are, you won’t survey as many people as you’d like to.
• It’s harder to generalize the results: With any qualitative study, because you’re dealing with a small pool of opinions, you can’t accurately say the views you gathered represent the views of a wider population.
• You need a skilled qualitative researcher: There are so many ways to accidentally influence the responses you get from a qualitative survey – your tone of voice, your rapport with the people you’re speaking to, and even the order in which you ask the questions. Unfortunately, the quality of the responses you get is largely based on how well the researchers conduct the interviews or focus groups.
• There’s no anonymity: Let’s face it, not everybody is comfortable talking about everything to everyone all the time. There are some topics that people will shy away from – especially in a one-on-one session or a discussion group full of strangers. If so, they’re likely to conceal their full answers if they’re feeling shy or judged, which will skew the results of your study. Some people might only be willing to do an anonymous quantitative study.

The benefits of quantitative research

• You get your hands on a larger sample: With a quantitative survey, a much broader study can be done – one which involves more people. Naturally, you’ll be able to more accurately generalize your results across an even wider group of people.
• You get objectivity and accuracy: There are far fewer variables involved with quantitative research. The data you’re collecting is often ‘close-ended’, which means people are choosing clear-cut multiple choice answers, such as yes/no, or Instagram/Facebook/TikTok. And when it comes to diving into the results, there’s no room for debate. A certain number of people do one thing, and a certain number of people do another.
• It’s faster and easier: With quantitative data collection, you can step into the world of automation. You don’t need a physical researcher to help – you simply opt for digital or mobile surveys. These can conduct thousands of interviews at the same time across multiple countries.
• You can save money: Because they’re quicker to run, quantitative methods are famously cost-effective. That’s why the cost of someone participating in a quantitative survey is typically far less than the price of a focus group. And you just need skilled researchers to write the survey, rather than conduct it.

The drawbacks of quantitative research:

• You get a less detailed picture: With this research method, results are based on numerical responses and, as a result, you get slightly less insight into the thoughts, motivations, and drivers of your group. You’re lacking a key component: context. To get around this, you can include ‘open-end’ answers, which allow a participant to write down more detailed responses rather than just ticking a box. But doing so relies on respondents having the time and truly understanding the question.
• It’s somewhat artificial: Quantitative research needs to be carried out in an unnatural environment so that it can be controlled. And while this is important, it means the results you gather might differ from ‘real world’ findings.
• You’re faced with limitations: A quantitative method needs to have pre-set answers, and sometimes, how a participant thinks, feels, or behaves might not be featured in the list. Their true answer is masked behind your lack of options, and it might push them to pick one that doesn’t really reflect how they feel.

Get the best of both worlds

Both approaches have strengths and weaknesses. By combining the two together (which is often referred to as mixed method research), you can seriously boost the quality and accuracy of your findings, adding both breadth and depth.

The advantages of mixed method research

• Enrich your story: You can use qualitative data to color the insights that were revealed in your quantitative survey.
• Examine your narrative: You can generate hypotheses from the opinions uncovered in qualitative research, then cross-reference these against a wider sample with a quantitative approach.
• Explain the surprises: You can use qualitative data to better understand any unexpected results from quantitative data.

How a combined approach can generate a results-driven campaign

Combining both data methods in a way that yields awesome results requires planning.

Like any successful data analysis, finding the right answers relies on asking the right questions.

And in order to ask the right questions, you need to identify your key goals – mapping out exactly what you want to achieve.

For example, companies looking to drive campaigns focused on ROI can use quantitative tracking tools like Google Analytics, Data Studio, or Power BI. If set up correctly, you can quickly uncover key performance indicators like website visits, time on page, traffic from social media, number of leads, and even revenue.

Pairing this with some qualitative information on how your customers feel about your brand – through questionnaires, reviews, case studies, or customer interviews will give you a detailed picture of what you need to know.

This kind of intelligence enables brands to gain a deep understanding of how well their campaigns are working and, critically, why.

Using qualitative analysis to streamline the user journey

Research can answer strategic business questions – but to do that well, you need to interrogate the information and gather the most actionable insight.

Qualitative analytics can give your brand answers around why a customer bought a certain product or service and what their end-to-end experience was like.

These findings provide clear data that can be actioned, enabling brands to do more of what’s working and address any kinks in the user journey.

Plus, qualitative proof like custome r reviews can help you drive more conversions. In fact:

99.9% of consumers read reviews, and 98% consider them an essential step on the consumer path to purchase.

So not only can qualitative research help you configure things behind the scenes, but it can also help you make more money. (As long as people are saying nice things about your brand.)

Using quantitative analysis to fix what’s broken

Quantitative analytics, on the other hand, can provide specific answers relating to how the purchase journey looks, enabling brands to spot any areas that are causing issues on touchpoints that matter.

For example, if a high percentage of buyers are dropping off on a certain page, or abandoning their basket at the same spot, marketers can address this pretty quickly, either by redesigning the page or making the transaction process faster.

Combining forces to make the magic happen

While quantitative data might flag issues around basket abandonment, ecommerce brands may still be unsure as to why consumers are dropping off.

Is the page a bit sluggish? Are the payment options confusing? Or is poor page design making the CTA hard to find?

Combining the hard numbers with the ‘why’ gives brands a clear idea of where the problems lie and how best to fix them.

Deeper insight gives a competitive edge

Combined research can be used in numerous ways depending on a brand’s business objectives.

For example, data might reveal that over-70s with disposable income and an interest in technology would buy more devices if the product designs accounted for failing eyesight and inhibited manual dexterity.

These sorts of insights could open up a whole new audience – and product category – giving brands more of a competitive edge.

Meeting the personalized future

Qualitative and quantitative research methods have different roles to play. Using the two together can be a powerful move, especially as consumer demand for personalization continues to rise.

To meet this demand, more and more brands and marketers are turning to audience profiling data , analyzing audience behaviors and perceptions on a massive scale, to tailor their activity to their consumers.

By combining qualitative personas with quantitative data, you can identify and define your audiences in as much detail as possible, understanding how, where, and when to reach them for maximum impact.

Never miss a post

By subscribing you confirm you’re happy for us to send you our latest articles.

Related articles

How consumers find new brands and research products in 2023, 6 ways brands are driving roi with in-house audience research, how kids are transforming tomorrow’s status quo, quick tips on finding the right data, faster, you’ve read our blog, now see our platform.

Every business has questions about its audiences, GWI has answers. Powered by consistent, global research, our platform is an on-demand window into their world.

How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

See our "Privacy Policy"

Ensure your structure and ideas are consistent and clearly communicated

Pair your Premium Editing with our add-on service Presubmission Review for an overall assessment of your manuscript.

André Queirós Higher Polytechnic Institute of Gaya, V. N. Gaia, Portugal

Daniel Faria Higher Polytechnic Institute of Gaya, V. N. Gaia, Portugal

Fernando Almeida Faculty of Engineering of Oporto University, INESC TEC, Porto, Portugal

.................................................

..................................................

Education Journals

European Journal Of Physical Education and Sport Science

European Journal of Foreign Language Teaching

European Journal of English Language Teaching

European Journal of Special Education Research

European Journal of Alternative Education Studies

European Journal of Open Education and E-learning Studies

Public Health Journals

European Journal of Public Health Studies

European Journal of Fitness, Nutrition and Sport Medicine Studies

European Journal of Physiotherapy and Rehabilitation Studies

Social Sciences Journals

European Journal of Social Sciences Studies

European Journal of Economic and Financial Research

European Journal of Management and Marketing Studies

European Journal of Human Resource Management Studies

European Journal of Political Science Studies

Literature, Language and Linguistics Journals

European Journal of Literature, Language and Linguistics Studies

European Journal of Literary Studies

European Journal of Applied Linguistics Studies

European Journal of Multilingualism and Translation Studies

...................................................

• Other Journals
• ##Editorial Board##
• ##Indexing and Abstracting##
• ##Author's guidelines##
• ##Covered Research Areas##
• ##Announcements##
• ##Related Journals##
• ##Manuscript Submission##

STRENGTHS AND LIMITATIONS OF QUALITATIVE AND QUANTITATIVE RESEARCH METHODS

Scientific research adopts qualitative and quantitative methodologies in the modeling and analysis of numerous phenomena. The qualitative methodology intends to understand a complex reality and the meaning of actions in a given context. On the other hand, the quantitative methodology seeks to obtain accurate and reliable measurements that allow a statistical analysis. Both methodologies offer a set of methods, potentialities and limitations that must be explored and known by researchers. This paper concisely maps a total of seven qualitative methods and five quantitative methods. A comparative analysis of the most relevant and adopted methods is done to understand the main strengths and limitations of them. Additionally, the work developed intends to be a fundamental reference for the accomplishment of a research study, in which the researcher intends to adopt a qualitative or quantitative methodology. Through the analysis of the advantages and disadvantages of each method, it becomes possible to formulate a more accurate, informed and complete choice.

Article visualizations:

Acocella, I. (2012). The focus group in social research: advantages and disadvantages. Quality & Quantity, 46(4), 1125-1136.

Almeida, F., & Monteiro, J. (2017). Approaches and principles for UX web experiences. International Journal of Information Technology and Web Engineering, 12(2), 49-65.

Alshenqeeti, H. (2014). Interviewing as a data collection method: a critical review. English Linguistics Research, 3(1), 39-45.

Atieno, O. (2009). An analysis of the strengths and limitation of qualitative and quantitative research paradigms. Problems of Education in the 21st Century, 13, 13-18.

Baxter, P., & Jack, S. (2008). Qualitative case study methodology: study design and implementation for novice researchers. The Qualitative Report, 13(4), 544-559.

Blackstone, A. (2012). Principles of sociological inquiry: qualitative and quantitative methods. Retrieved from https://2012books.lardbucket.org/books/sociological-inquiry-principles-qualitative-and-quantitative-methods/index.html

Borrego, M., Douglas, E., & Amelink, C. (2009). Quantitative, qualitative, and mixed research methods in engineering education. Journal of Engineering Education, 98(1), 53-66.

Castellan, C. (2010). Quantitative and qualitative research: a view for clarity. International Journal of Education, 2(2), 1-14.

Charmaz, K. (2006). Constructing grounded theory: a practical guide through qualitative analysis. London, United Kingdom: Sage.

Choy, L. (2014). The strengths and weaknesses of research methodology: comparison and complimentary between qualitative and quantitative approaches. IOSR Journal of Humanities and Social Science, 19(4), 99-104.

Coughlan, M., Cronin, P, & Ryan, F. (2007). Step-by-step guide to critiquing research. Part 1: quantitative research. British Journal of Nursing, 16(11), 658-663.

Crescentini, A. & Mainardi, G. (2009). Qualitative research articles: guidelines, suggestions and needs. Journal of Workplace Learning, 21(5), 431-439.

Creswell, J. (2013). Research design: qualitative, quantitative, and mixed methods approaches. London, United Kingdom: Sage.

Creswell, J. & Poth, C. (2017). Qualitative inquiry and research design: choosing among five approaches. London, United Kingdom: Sage.

Davies, M. (2011). Concept mapping, mind mapping and argument mapping: what are the differences and do they matter? Higher Education, 62(3), 279-301.

Etikan, I., Musa, S., & Alkassim, R. (2016). Comparison convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4.

Flanagan, T. (2013). The scientific method and why it matters. C2C Journal, 7(1), 4-6.

Felix, E. (2015). The implications of parametric and non-parametric statistics in data analysis in marketing research. International Journal of Humanities and Social Science, 5(6), 74-83.

Hoy, W. & Adams, C. (2015). Quantitative research in education. London, United Kingdom: Sage.

Jamshed, S. (2014). Qualitative research method - interviewing and observation. Journal of Basic and Clinical Pharmacy, 5(4), 87-88.

Kelley, K., Clark, B., Brown, V., & Sitzia, J. (2003). Good practice in the conduct and reporting of survey research. International Journal for Quality in Health Care, 15(3), 261-266.

Kothari, C. (2013). Research methodology: methods and techniques. New Delhi, India: New Age International.

Maher, J., Markey, J., & Ebert-May, D. (2013). The other half of the story: effect size analysis in quantitative research. CBE Life Sciences Education, 12(3), 345-351.

Martin, W., & Bridgmon, K. (2012). Quantitative and statistical research methods: from hypothesis to results. New Jersey, USA: Jossey-Bass.

Maxwell, J. (2013). Qualitative research design: an interactive approach. London, United Kingdom: Sage.

Merriam, S. & Tisdell, E. (2015). Qualitative research: a guide to design and implementation. New Jersey, USA: Jossey-Bass.

Mori, H. & Nakayama, T. (2013). Academic impact of qualitative studies in healthcare: bibliometric analysis. Plos One, 8(3), 1-7.

Moriarty, J. (2011). Qualitative methods overview. London, UK: NIHR School for Social Care Research.

Noble, H., & Smith, J. (2015). Issues of validity and reliability in qualitative research. Evidence-Based Nursing, 18(2), 34-5.

Nurani, L. (2008). Critical review of ethnographic approach. Jurnal Sosioteknologi, 7(14), 441-447.

Oppong, S. (2013). The problem of sampling in qualitative research. Asian Journal of Management Sciences and Education, 2(2), 202-210.

Polit, D., & Beck C. (2006). Essentials of nursing research: methods, appraisal and utilization. Philadelphia, USA: Lippincott Willaims and Wilkins.

Ponelis, S. (2015). Using interpretive qualitative case studies for exploratory research in doctoral studies: a case of information systems research in small and medium enterprises. International Journal of Doctoral Studies, 10, 535-550.

Rahman, S. (2017). The advantages and disadvantages of using qualitative and quantitative approaches and methods in language "testing and assessment" research: a literature review. Journal of Education and Learning, 6(1), 102-112.

Roshan, B. & Deeptee, P. (2009). Justifications for qualitative research in organisations: a step forward. The Journal of Online Education, 1, 1-7.

Schneider, J. (2013). Caveats for using statistical significance tests in research assessment. Journal of Informetrics, 7(1), 50-62.

Starman, A. (2013). The case study as a type of qualitative research. Journal of Contemporary Educational Studies, 1, 28-43.

Williams, C. (2007). Research methods. Journal of Business & Economic Research, 5(3), 65-72.

• There are currently no refbacks.

Copyright © 2015-2023. European Journal of Education Studies (ISSN 2501 - 1111) is a registered trademark of Open Access Publishing Group . All rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number ( ISSN ) serial number certificate issued by Romanian National Library ( Biblioteca Nationala a Romaniei ). All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All authors who send their manuscripts to this journal and whose articles are published on this journal retain full copyright of their articles. All the research works published on this journal are meeting the  Open Access Publishing  requirements and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a  Creative Commons Attribution 4.0 International License (CC BY 4.0) .

9 methodologies for a successful qualitative research assignment

Qualitative research is important in the educational and scientific domains. It enables a deeper understanding of phenomena, experiences, and context. Many researchers employ such research activities in the fields of history, sociology, and anthropology. For such researchers, learning quality analysis insights is crucial. This way, they can perform well throughout their research journey. Writing a qualitative research assignment is one such way to practice qualitative interpretations. When students address various qualitative questions in these projects, they become efficient in conducting these activities at a higher level, such as for a master’s or Ph.D. thesis.

The FormPlus highlights why researchers prefer qualitative research over quantitative research. It is faster, scientific, objective, focused, and acceptable. Researchers who don’t know what to expect from the research outcomes usually choose qualitative research. In this guide, we will discuss the top methodologies that students can employ while writing their qualitative research assignments. This way, you can write an appealing document that perfectly demonstrates your qualitative research skills.

However, being stressed with academic and daily life commitments, if you find it challenging to manage time exclusively for such projects, availing of assignment writing services can make it manageable. Instead of doing anything wrong in the hustle, get it done by the professionals specifically working to handle these academic write-ups. Now, let’s define quality research before we discuss the actual topic.

What is meant by qualitative research?

Quality research is a market research method that gathers data from conversational and open-ended communication. In simple words, it is about what people think and why they think so. It relates to the nature or standard of something rather than dealing with its quantity. Such researchers collect nonnumerical data to understand opinions, concepts, and ideas.

How do you write a qualitative research assignment? Top 9 methodologies

Writing an assignment requires your command of various tasks. Qualitative research assignment design involves research, writing, structuring, and providing citations of the resources used. Assignment writing plays a crucial role in upgrading your grades.

So, you must make it accurate and authentic. Write it with the utmost care without skipping any important aspects. Sometimes, it can be hard, but it becomes easy if you correctly use effective methodologies. This is why we have brought together some of the common methodologies you can use to write your qualitative research assignments.

1. Interviews

A qualitative interview is mostly used in projects that involve market research. In this study personal interaction is required to collect in-depth information of the participants. In qualitative research for assignment, consider the interview as a personal form of research agenda rather than a focused group study. A qualitative interview requires careful planning so that you can gather meaningful data.

Here are the simple steps to consider for its implementation in a qualitative research assignment:

• Define research objectives.
• Identify the target population.
• Obtain informed consent of participants.
• Make an interview guideline.
• Select a suitable location.
• Conduct the interview.
• Show respect for participant’s perspectives.
• Analyse the data.

2. Observation

In qualitative observation, the researcher gathers data from five senses: sight, hearing, touch, smell, and taste. It is a subject approach that depends on the sensory organ of the researcher. This method allows you to better understand the culture, process, and people under study. Some of its characteristics to consider for writing a qualitative research assignment include,

• It is a naturalistic inquiry of the participants in a natural environment.
• This approach is subjective and depends on the researcher’s observation.
• It does not seek a definite answer to a query.
• The researcher can recognise their own biases when compiling findings.

3. Questionnaires

In this type of survey, the researcher asks open-ended questions to participants. This way, they price the long written or typed document. In writing qualitative research assignments, these questions aim to reveal the participants’ narratives and experiences. Once you know what type of information you need, you can start curating your questionnaire form. The questions must be specific and clear enough that the participants can comprehend them.

Below are the main points that must be considered when creating qualitative research questionnaires.

• Avoid jargon and ambiguity in the questions.
• Each question should contribute to the research objectives.
• Use simple language.
• The questions should be neutral and unbiased.
• Be precise, as the complex questions can overwhelm the respondents.
• Always conduct a pilot test.
• Put yourself in the respondent’s shoes while asking questions.

4. Case Study

A case study is a detailed analysis of a person, place, thing, organisation, or phenomenon. This method is appropriate when you want to gain a contextual, concrete, and in-depth understanding of the real-world problem for writing your qualitative research assignment. This method is especially helpful when you need more time to conduct large-scale research activities.

The four crucial steps below can be followed up with this methodology.

• Select a case that has the potential to provide new and unexpected insights into the subject.
• Make a theoretical framework.
• Collect your data from various primary and secondary resources.
• Describe and analyse the case to provide a clear picture of the subject.

5. Focus Groups

Focused group research has some interesting properties. In this method, a planned interview is conducted within a small group. For this purpose, some of the participants are sampled from the study population to record data for writing a qualitative research assignment. Typically, a focused group has features like,

• At least four to ten participants must meet for up to two hours.
• There must be a facilitator who can guide the discussion by asking open-ended questions.
• The emphasis must be put on the group discussion rather than the discussion of the group members with the facilitator.
• The discussion should be recorded and transcribed by the researchers.

6. Ethnographic Research

It is the most in-depth research method that involves studying people in their natural environment. It requires the researcher to adopt the target audience environment. The environment can be anything from an organisation to a city or any remote location.

However, the geographical constraints can be a problem in this study. For students who are writing their qualitative research assignment, some of the features of ethnographic research to write in their document include,

• The researcher can get a more realistic picture of the study.
• It uncovers extremely valuable insights.
• Provides accurate predictions.
• You can extend the observation to create more in-depth data.
• You can interact with people within a particular context.

7. Record Keeping

This method is similar to going to the library to collect data from books. You consult various relayed books, note the important points, and take note of the referencing. So, the researcher uses already existing data rather than introducing new things in the field.

Later on, this data can be used to conduct new research. Yet, when faced with the vast resources available in your institution’s library, seeking assistance from UK-based assignment writing services is an excellent solution if you need help pinpointing the most relevant information for your topic. Proficient in data gathering and adept at structuring qualitative research assignments, these professionals can significantly elevate your academic results.

This method is mostly used by companies to understand a group of customers’ behaviour, characteristics, and motivation. It allows respondents to ask in-depth questions about their experience. In a business market, it helps you understand how your customers make decisions. The intent is to understand them at their level and make related changes in your setup. The researcher must ask generic and precise questions that have a clear purpose.

Consider the below examples of qualitative survey questions. It can be useful in recording data and writing qualitative research assignments.

• Why did you buy this skin care product?
• What is the overall narrative of this brand?
• How do you feel after buying this product?
• What sets this brand apart from others?
• How will this product fulfil your needs?
• What are the things that you expect from this brand to grant you?

9. Action Research

This method involves collaboration and empowerment of the participants. It is mostly appropriate for marginalised groups where there is no flexibility.

The primary characteristics of the action research that can be quoted in your qualitative research assignment include,

• It is action-oriented, and participants are actively involved in the research.
• There is a collaborative process between participants and researchers.
• The nature of action research is flexible to the changing situation.

However, the survey also accompanies some of the limitations, including,

• The researcher can misinterpret the open-ended questions.
• The data ownership between the researcher and participants needs to be negotiated.
• The ethical considerations must be kept.
• It is not considered a scientific method as it is fluid in data collection. Consequently, it may not attract the finding.

What is the difference between quantitative and qualitative research?

Both research types share the common aim of knowledge acquisition. In quantitative research, the use of numbers and objective measures is used. It seeks answers to questions like when and where.

On the other hand, in qualitative research, the researcher is concerned with subjective phenomena. Such data can’t be numerically measured. For example, you might conduct a survey to analyse how different people experience grief.

What are the 4 types of qualitative research?

There are various types of qualitative research. It may include,

● Phenomenological studies:

It examines the human experience via description provided by the people involved. These are the lived experiences of the people. It is usually used in research areas where little knowledge is known.

● Ethnographic studies:

It involves the analysis of data about cultural groups. In such analysis, the researcher mostly lives with different communities and becomes part of their culture to provide solid interpretations.

● Grounded theory studies:

In this qualitative approach, the researcher collects and analyses the data. Later on, a theory is developed that is grounded in the data. It used both inductive and deductive approaches for theory development.

● Historical studies:

It is concerned with the location, identification, evaluation, and synthesis of data from the past. These researchers are not concerned with discovering past events but with relating these events to the present happenings.

The Research Gate provides a flow chart illustrating various qualitative research methods.

What are The 7 characteristics of qualitative research?

The following are some of the distinct features of qualitative research. You can write about them in your qualitative research assignment, as they are collected from reliable sources.

• It can even capture the changing attitude within the target group.
• It is beyond the limitations associated with quantitative research
• It explains something that numbers alone can’t describe.
• It is a flexible approach to improve the outcomes.
• A researcher is not supposed to become more speculative about the results.
• This approach is more targeted.
• It keeps the cost of data collection down.

What are the advantages and disadvantages of qualitative research?

The pros of qualitative research can’t be denied. However, some cons are also associated with this research.

• Explore attitudes and behaviours in depth.
• It encourages discussions for better results.
• Generate descriptive data that can formulate new theories.
• The small sample size can be a problem.
• Bias in the sample collection.
• Lack of privacy if you are covering a sensitive topic.

Qualitative research assignment examples

The Afe Babalola University ePortal provides an example of a qualitative assignment. Here is the description of quality questions and related answers. You can get an idea about how to handle your quality research assignment project with this sample.

The questions asked in the paper are displayed below.

The Slide Team presents a template for further compressing other details, such as the qualitative research assignment template. You can use it to make your presentation look professional.

Writing a qualitative research assignment is crucial, especially if you want to engage in research activities for your master’s thesis. Most researchers choose this method because of the associated credibility and reliability of the results. In the above guide, we have discussed some of the prominent features of this method. All of the given data can help you in writing your assignments. We have discussed the benefits of each methodology and a brief account of how you can carry it.

However, even after going through this whole guideline, if the concepts of the Qualitative Research methods assignment seem ambiguous and you think you can’t write a good project, then ask professional to “ write my assignment .” These experts can consult the best sources for the data collection of your project. Consequently, they will deliver you the winning document that can stand out among other write-ups.