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• What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

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Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

• In descriptive research , you simply seek an overall summary of your study variables.
• In correlational research , you investigate relationships between your study variables.
• In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

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Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

• Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

• Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

• Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

• Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

• Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

• Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

• Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

• Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

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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
• 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 .

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.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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In This Article Expand or collapse the "in this article" section Quantitative Research Designs in Educational Research

Introduction, general overviews.

• Survey Research Designs
• Correlational Designs
• Other Nonexperimental Designs
• Randomized Experimental Designs
• Quasi-Experimental Designs
• Single-Case Designs
• Single-Case Analyses

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• Methodologies for Conducting Education Research
• Mixed Methods Research
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• Qualitative Data Analysis Techniques
• Qualitative, Quantitative, and Mixed Methods Research Sampling Strategies
• Researcher Development and Skills Training within the Context of Postgraduate Programs
• Single-Subject Research Design
• Social Network Analysis
• Statistical Assumptions

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Quantitative Research Designs in Educational Research by James H. McMillan , Richard S. Mohn , Micol V. Hammack LAST REVIEWED: 29 July 2020 LAST MODIFIED: 24 July 2013 DOI: 10.1093/obo/9780199756810-0113

The field of education has embraced quantitative research designs since early in the 20th century. The foundation for these designs was based primarily in the psychological literature, and psychology and the social sciences more generally continued to have a strong influence on quantitative designs until the assimilation of qualitative designs in the 1970s and 1980s. More recently, a renewed emphasis on quasi-experimental and nonexperimental quantitative designs to infer causal conclusions has resulted in many newer sources specifically targeting these approaches to the field of education. This bibliography begins with a discussion of general introductions to all quantitative designs in the educational literature. The sources in this section tend to be textbooks or well-known sources written many years ago, though still very relevant and helpful. It should be noted that there are many other sources in the social sciences more generally that contain principles of quantitative designs that are applicable to education. This article then classifies quantitative designs primarily as either nonexperimental or experimental but also emphasizes the use of nonexperimental designs for making causal inferences. Among experimental designs the article distinguishes between those that include random assignment of subjects, those that are quasi-experimental (with no random assignment), and those that are single-case (single-subject) designs. Quasi-experimental and nonexperimental designs used for making causal inferences are becoming more popular in education given the practical difficulties and expense in conducting well-controlled experiments, particularly with the use of structural equation modeling (SEM). There have also been recent developments in statistical analyses that allow stronger causal inferences. Historically, quantitative designs have been tied closely to sampling, measurement, and statistics. In this bibliography there are important sources for newer statistical procedures that are needed for particular designs, especially single-case designs, but relatively little attention to sampling or measurement. The literature on quantitative designs in education is not well focused or comprehensively addressed in very many sources, except in general overview textbooks. Those sources that do include the range of designs are introductory in nature; more advanced designs and statistical analyses tend to be found in journal articles and other individual documents, with a couple exceptions. Another new trend in educational research designs is the use of mixed-method designs (both quantitative and qualitative), though this article does not emphasize these designs.

For many years there have been textbooks that present the range of quantitative research designs, both in education and the social sciences more broadly. Indeed, most of the quantitative design research principles are much the same for education, psychology, and other social sciences. These sources provide an introduction to basic designs that are used within the broader context of other educational research methodologies such as qualitative and mixed-method. Examples of these textbooks written specifically for education include Johnson and Christensen 2012 ; Mertens 2010 ; Arthur, et al. 2012 ; and Creswell 2012 . An example of a similar text written for the social sciences, including education that is dedicated only to quantitative research, is Gliner, et al. 2009 . In these texts separate chapters are devoted to different types of quantitative designs. For example, Creswell 2012 contains three quantitative design chapters—experimental, which includes both randomized and quasi-experimental designs; correlational (nonexperimental); and survey (also nonexperimental). Johnson and Christensen 2012 also includes three quantitative design chapters, with greater emphasis on quasi-experimental and single-subject research. Mertens 2010 includes a chapter on causal-comparative designs (nonexperimental). Often survey research is addressed as a distinct type of quantitative research with an emphasis on sampling and measurement (how to design surveys). Green, et al. 2006 also presents introductory chapters on different types of quantitative designs, but each of the chapters has different authors. In this book chapters extend basic designs by examining in greater detail nonexperimental methodologies structured for causal inferences and scaled-up experiments. Two additional sources are noted because they represent the types of publications for the social sciences more broadly that discuss many of the same principles of quantitative design among other types of designs. Bickman and Rog 2009 uses different chapter authors to cover topics such as statistical power for designs, sampling, randomized controlled trials, and quasi-experiments, and educational researchers will find this information helpful in designing their studies. Little 2012 provides a comprehensive coverage of topics related to quantitative methods in the social, behavioral, and education fields.

Arthur, James, Michael Waring, Robert Coe, and Larry V. Hedges, eds. 2012. Research methods & methodologies in education . Thousand Oaks, CA: SAGE.

Readers will find this book more of a handbook than a textbook. Different individuals author each of the chapters, representing quantitative, qualitative, and mixed-method designs. The quantitative chapters are on the treatment of advanced statistical applications, including analysis of variance, regression, and multilevel analysis.

Bickman, Leonard, and Debra J. Rog, eds. 2009. The SAGE handbook of applied social research methods . 2d ed. Thousand Oaks, CA: SAGE.

This handbook includes quantitative design chapters that are written for the social sciences broadly. There are relatively advanced treatments of statistical power, randomized controlled trials, and sampling in quantitative designs, though the coverage of additional topics is not as complete as other sources in this section.

Creswell, John W. 2012. Educational research: Planning, conducting, and evaluating quantitative and qualitative research . 4th ed. Boston: Pearson.

Creswell presents an introduction to all major types of research designs. Three chapters cover quantitative designs—experimental, correlational, and survey research. Both the correlational and survey research chapters focus on nonexperimental designs. Overall the introductions are complete and helpful to those beginning their study of quantitative research designs.

Gliner, Jeffrey A., George A. Morgan, and Nancy L. Leech. 2009. Research methods in applied settings: An integrated approach to design and analysis . 2d ed. New York: Routledge.

This text, unlike others in this section, is devoted solely to quantitative research. As such, all aspects of quantitative designs are covered. There are separate chapters on experimental, nonexperimental, and single-subject designs and on internal validity, sampling, and data-collection techniques for quantitative studies. The content of the book is somewhat more advanced than others listed in this section and is unique in its quantitative focus.

Green, Judith L., Gregory Camilli, and Patricia B. Elmore, eds. 2006. Handbook of complementary methods in education research . Mahwah, NJ: Lawrence Erlbaum.

Green, Camilli, and Elmore edited forty-six chapters that represent many contemporary issues and topics related to quantitative designs. Written by noted researchers, the chapters cover design experiments, quasi-experimentation, randomized experiments, and survey methods. Other chapters include statistical topics that have relevance for quantitative designs.

Johnson, Burke, and Larry B. Christensen. 2012. Educational research: Quantitative, qualitative, and mixed approaches . 4th ed. Thousand Oaks, CA: SAGE.

This comprehensive textbook of educational research methods includes extensive coverage of qualitative and mixed-method designs along with quantitative designs. Three of twenty chapters focus on quantitative designs (experimental, quasi-experimental, and single-case) and nonexperimental, including longitudinal and retrospective, designs. The level of material is relatively high, and there are introductory chapters on sampling and quantitative analyses.

Little, Todd D., ed. 2012. The Oxford handbook of quantitative methods . Vol. 1, Foundations . New York: Oxford Univ. Press.

This handbook is a relatively advanced treatment of quantitative design and statistical analyses. Multiple authors are used to address strengths and weaknesses of many different issues and methods, including advanced statistical tools.

Mertens, Donna M. 2010. Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods . 3d ed. Thousand Oaks, CA: SAGE.

This textbook is an introduction to all types of educational designs and includes four chapters devoted to quantitative research—experimental and quasi-experimental, causal comparative and correlational, survey, and single-case research. The author’s treatment of some topics is somewhat more advanced than texts such as Creswell 2012 , with extensive attention to threats to internal validity for some of the designs.

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Quantitative Research in Education A Primer

• Wayne K. Hoy - Ohio State University, USA
• Curt M. Adams - University of Oklahoma, USA
• Description

“ The book provides a reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research… ”

— Megan Tschannen-Moran, The College of William & Mary

Quantitative Research in Education: A Primer, Second Edition is a brief and practical text designed to allay anxiety about quantitative research. Award-winning authors Wayne K. Hoy and Curt M. Adams first introduce readers to the nature of research and science, and then present the meaning of concepts and research problems as they dispel notions that quantitative research is too difficult, too theoretical, and not practical. Rich with concrete examples and illustrations, the Primer emphasizes conceptual understanding and the practical utility of quantitative methods while teaching strategies and techniques for developing original research hypotheses.

The Second Edition includes suggestions for empirical investigation and features a new section on self-determination theory, examples from the latest research, a concluding chapter illustrating the practical applications of quantitative research, and much more. This accessible Primer is perfect for students and researchers who want a quick understanding of the process of scientific inquiry and who want to learn how to effectively create and test ideas.

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

For assistance with your order: Please email us at [email protected] or connect with your SAGE representative.

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“This text will definitely be useful in providing students with a solid orientation to research design particularly in quantitative research”

“Precision, precision, precision! I think this is a must have companion text for graduate students who have to complete a thesis or dissertation. The author does an outstanding job of cataloging and describing difficult research methods terms in a clear and concise way.”

“Greatest strength is the comprehensiveness of the treatment”

“A reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research”

Provides all the essential information for quantitative research in a concise book.

A book on research in education but quite well can be accommodated into other social science areas. A great easy to follow publication especially if someone is new to statistical analysis.

There are two strong chapters in this publication that are clearer and more relevant that the sources presently being used by my students. Chapter 3 is particularly well written and clear and builds a progression in terms of understanding statistics. Chapter 4 is also effective however I would probably place this before Chapter 3. In terms of detail there is probably too much in Chapter 4 on Hypothesis whereas Chapter 3 could be developed perhaps by the inclusion of more examples.

Very helpful book that provides a basis for students undertaking education based research.

For those that are interested in doing research that is quantitative in nature, this book is useful, although we tend to advise a more qualitative approach. Therefore I can see myself dipping in and out of this book as it provides some good explanations and there is follow through. I would have welcomed more working examples as this would have concretised everything a lot more.

This is a good supplement to the research methods module, especially for those students who are entering into the field of education. The quantitative methods discussed are also transferrable to other subjects.

NEW TO THIS EDITION:    

• A new chapter devoted to the practical applications of education research uses the concepts of collective trust, organizational climate, and improvement science to illustrate the utility of a quantitative approach. It also offers guidelines for analyzing and improving the practice of research in education.
• New hypotheses found in a variety of research studies are available for readers to analyze and diagram.
• A new section on self-determination theory has been added to demonstrate the relation between theory and practice.
• A new section on self-regulatory climate gives readers an opportunity to explore an exciting new area that they are likely to encounter in practice.  
• A conceptual description of Hierarchical Linear Modeling (HLM) has been added to help readers understand statistical data organized at more than one level.    

KEY FEATURES:  

• Education-specific concrete examples bring concepts to life and engage readers with relevant, meaningful illustrations.
• Check Your Understanding exercises and questions assess the reader’s ability to understand, value, and apply the content of the chapter.  
• Strat egies and techniques for generating hypotheses help readers understand the process of creating their own hypotheses.
• Key Terms are highlighted in the text when they first appear and then summarized in a list at the end of the chapter to help reinforce key concepts.
• A Glossary concisely and clearly defines all the key terms in the text so readers have immediate access to ideas and concepts needing review.
• Charts throughout the text allow readers to select appropriate statistical techniques for given scenarios.
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Quantitative Research in Research on the Education and Learning of Adults

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• Ellen Boeren 13  

Part of the book series: Lifelong Learning Book Series ((LLLB,volume 24))

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This chapter starts from the observation that there is a limited presence of quantitative research published in leading adult education journals such as Adult Education Quarterly , Studies in Continuing Education and International Journal of Lifelong Learning . This observation was also discussed by Fejes and Nylander (2015, see also Chap. 7 ). As an adult education scholar mainly working with large quantitative datasets, I aim to provide more insight on what quantitative methods have to offer to the field. I will do this through a brief discussion of the role of methodologies and methods in empirical research, but also by engaging with examples of quantitative research available in the scholarly literature, including a range of existing quantitative scales, and how these can be taken forward in new research as tools to generate the construction of new knowledge. I will first explore potential reasons why the presence of quantitative research in the leading generic adult education journals is so limited.

This chapter is a revised version of a previousely published article: Boeren, E. (2018) The Methodological Underdog: A Review of Quantitative Research in the Key Adult Education Journals. Adult Education Quarterly , 68(1), 63–79.

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Boeren, E. (2019). Quantitative Research in Research on the Education and Learning of Adults. In: Fejes, A., Nylander, E. (eds) Mapping out the Research Field of Adult Education and Learning. Lifelong Learning Book Series, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-030-10946-2_8

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

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

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

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

Qualitative vs. Quantitative Research in Education: Definitions

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

Generate Hypotheses with Qualitative Research

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

Form Strong Conclusions with Quantitative Research

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

Differences in Data Collection Methods

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

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

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

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

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

Qualitative Research Methods

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

Quantitative Research Methods

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

Choosing a Research Strategy

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

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

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

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

Learn How to Put Education Research into Action

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

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

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Quantitative Research in Education

2023, Interdisciplinary Research: Collaborative Insights

In the past few decades, educational practices have changed drastically, particularly regarding how information and learning are delivered and processed. Education research frequently employs quantitative methods. Quantitative education research provides numerical data that can prove or disprove a theory, and administrators can easily share the quantitative findings with other academics and districts. While the study may be based on relative sample size, educators and researchers can extrapolate the results from quantitative data to predict outcomes for larger student populations and groups. Educational research has a long history of utilising measurement and statistical methods. Commonly quantitative methods encompass a variety of statistical tests and instruments. Educators and students could transition to the digital era and research-based knowledge, including quantitative research in advanced higher education, as the technology has advanced. The quantitative research methods in education emphasise basic group designs for research and evaluation, analytic methods for exploring relationships between categorical and continuous measures, and statistical analysis procedures for group design data. The essential is to evaluate quantitative analysis and provide the research process, sampling techniques, the advantages and disadvantages of quantitative research in the article.

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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.

Quantitative Research, Assessment, and Evaluation in Education Certificate

Graduate Certificate

The courses for the Quantitative Research, Assessment, and Evaluation in Education (QRAE) Certificate post to the student’s transcript as a separate area of work. Courses should be chosen from the “Program Requirements” list below. Most of the courses are currently offered in face-to-face or hybrid format. This certificate program accepts applications from Purdue University graduate students from any Purdue West Lafayette graduate programs.

This program has rolling admission. Applications must be fully complete and submitted (including all required materials) and all application fees paid prior to the deadline in order for applications to be considered and reviewed. For a list of all required materials for this program application, please see the “Admissions” section below.

• July 1 is the deadline for Fall applications.
• November 15 is the deadline for Spring applications.
• March 15 is the deadline for Summer applications.

This program does not lead to licensure in the state of Indiana or elsewhere. Contact the College of Education Office of Teacher Education and Licensure (OTEL) at [email protected] before continuing with program application if you have questions regarding licensure or contact your state Department of Education about how this program may translate to licensure in your state of residence.

APPLICATION PROCEDURE

Application Instructions for the Quantitative Research, Assessment, and Evaluation Certificate program from the Office of Graduate Studies:

In addition to a submitted application (and any applicable application fees paid), the following materials are required for admission consideration, and all completed materials must be submitted by the application deadline in order for an application to be considered complete and forwarded on to faculty and the Purdue Graduate School for review.

Here are the materials required for this application:

• Official, current Purdue transcripts
• Graduate School Form 18 for Dual Enrolled students. Please upload this form with your application with your signature and information only. Our office will obtain the necessary faculty signatures.
• Academic Statement of Purpose
• Personal History Statement

We encourage prospective students to submit an application early, even if not all required materials are uploaded. Applications are not forwarded on for faculty review until all required materials are uploaded.

When submitting your application for this program, please select the following options:

• Select a Campus: Purdue West Lafayette (PWL)
• Select your proposed graduate major: Educational Studies
• Please select an Area of Interest: Educational Psychology
• Please select a Degree Objective: Quantitative Research Graduate Certificate
• Primary Course Delivery: Residential

Program Requirements

There is a five-year time limit for completion of the QRAE Certificate Program, beginning in the semester when the first elective course is taken. To earn the certificate, students must complete all courses with an “A” or “B” grade.

Prerequisite Courses

EDPS 53300 – Introduction to Educational Research I: Methodology (or equivalent course) EDPS 55600 – Introduction to Quantitative Data Analysis Methods in Education I (or equivalent course) EDPS 55700 – Introduction to Quantitative Data Analysis Methods in Education II (or equivalent course)

12 Credit Hours of Coursework (choose among the following)

EDPS 53100 – Introduction to Measurement and Instrument Design EDPS 63200 – Seminar in Research Procedures in Education – Recent topics include Meta-analysis, Structural Equation Modeling, Computerized Adaptive Testing, Multilevel Modeling (variable title; can be taken multiple times) EDPS 63500 – Psychometric Theory and Application EDPS 63600 – Item Response Theory EDPS 63800 – Factor Analytic Procedures

Course Content Information or Blackboard: Contact Dr. Yukiko Maeda Course Registration, payment, drops/withdraws, and removing holds: [email protected] Career accounts: ITaP (765) 494-4000

Science & Quantitative Reasoning Education

Yale undergraduate research, student-developed ai chatbot opens yale philosopher’s works to all.

LuFlot Bot, a generative AI chatbot trained on the works of Yale philosopher Luciano Floridi, answers questions on the ethics of digital technology.