quantitative research title structure

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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
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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.

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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

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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.

• What is the demographic makeup of Singapore in 2020?
• How has the average temperature changed globally over the last century?
• Does environmental pollution affect the prevalence of honey bees?
• Does working from home increase productivity for people with long commutes?

Table of contents

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.

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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Handbook of Research Methods in Health Social Sciences pp 985–997 Cite as

Writing Quantitative Research Studies

• Ankur Singh 2 ,
• Adyya Gupta 3 &
• Karen G. Peres 4  
• Reference work entry
• First Online: 13 January 2019

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Summarizing quantitative data and its effective presentation and discussion can be challenging for students and researchers. This chapter provides a framework for adequately reporting findings from quantitative analysis in a research study for those contemplating to write a research paper. The rationale underpinning the reporting methods to maintain the credibility and integrity of quantitative studies is outlined. Commonly used terminologies in empirical studies are defined and discussed with suitable examples. Key elements that build consistency between different sections (background, methods, results, and the discussion) of a research study using quantitative methods in a journal article are explicated. Specifically, recommended standard guidelines for randomized controlled trials and observational studies for reporting and discussion of findings from quantitative studies are elaborated. Key aspects of methodology that include describing the study population, sampling strategy, data collection methods, measurements/variables, and statistical analysis which informs the quality of a study from the reviewer’s perspective are described. Effective use of references in the methods section to strengthen the rationale behind specific statistical techniques and choice of measures has been highlighted with examples. Identifying ways in which data can be most succinctly and effectively summarized in tables and graphs according to their suitability and purpose of information is also detailed in this chapter. Strategies to present and discuss the quantitative findings in a structured discussion section are also provided. Overall, the chapter provides the readers with a comprehensive set of tools to identify key strategies to be considered when reporting quantitative research.

• Quantitative analysis
• Research methodology
• Writing strategies
• Empirical studies

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Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia

Ankur Singh

School of Public Health, The University of Adelaide, Adelaide, SA, Australia

Adyya Gupta

Australian Research Centre for Population Oral Health (ARCPOH), Adelaide Dental School, The University of Adelaide, Adelaide, SA, Australia

Karen G. Peres

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Pranee Liamputtong

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Singh, A., Gupta, A., Peres, K.G. (2019). Writing Quantitative Research Studies. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_117

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Structure for research articles (quantitative and mixed methods).

Maximum length: 3,000 words.

Descriptive title

The title should include a core finding or argument of the article.

Article’s lead  [50 to 100 words]

The “lead” of an article attracts the curiosity of the readers. It presents one or two highlights from the article. For example, the lead could focus on one of the most important findings or implications discussed in the paper. This is NOT an abstract and it should NOT provide a comprehensive overview of the paper.

Research questions

Summarize your research questions in bullet points (no more than 4).

Essay summary  [200 words]     

• Summarize the research methods you used in one or two sentences (surveys, experiments, interviews, observations, document analysis, etc.).
• Summarize the most important findings of this study in one or two sentences each.
• Summarize the real-world implications of this study in one or two sentences each.

Implications  [1,000 words]

First, briefly present the key argument(s) that you are deriving from your findings in formatting and language that are easily understandable for a non-specialist audience with a professional interest in misinformation (e.g., journalists, educators, policymakers, politicians).

Second, discuss the significance and implications of your argument and findings. What recommendations can you provide, and to whom, based on your argument and findings? For example, can your argument and findings inform the design of novel policies, infrastructural interventions, or educational programs? 

Remember: Use clear, accessible language that avoids academic jargon.

Findings  [1,000 words]

This section corresponds to the “findings or results” section of a traditional academic publication. However, you must present your findings in formatting and language that are easily understandable for a non-specialist audience with a professional interest in misinformation.

To complete this section:

• List and describe the key findings or major points, from the more generalizable to the more specific;
• Each finding should be separately described in one or two paragraphs; 
• Start each paragraph with a topic sentence, then describe the finding(s) with a few sentences;
• Add as many paragraphs and findings as needed, within the word limit;
• Add images, data, tables, videos, and audio files “inline” immediately after the paragraph presenting the corresponding finding or set of findings (for non-embeddable interactive files, mark where in the text they should appear and send a link to the file itself separately).

Finding 1: …  (state your most important finding/point in one sentence)

CONTENT (describe this finding in a few sentences)

CORRESPONDING VISUAL (add if necessary)

Finding 2: …  (state your next most important finding/point in one sentence)

Methods  [500 to 1,000 words]

This section corresponds to the “research design and methods” sections of a traditional academic publication.

Please answer the following questions (when appropriate):

• What are your research questions? (mandatory)
• What hypotheses did you investigate or test? (if appropriate)
• What methods for data collection and analysis did you use? (mandatory)
• How did you select your population sample? (if appropriate)
• How and why are these methods appropriate to answer your research questions? (mandatory)

NOTE: If you need more space to describe your methodology, submit a separate methodology appendix. The appendix has no word limit. Supplemental appendices should be included in the text of the submission (after the Data Availability statement) AND submitted as separate files. Please use our template for appendices when submitting.

Bibliography

All citations must be listed at the end of the text file, in alphabetical order of authors’ surnames. Citations should be submitted in APA 7 format (Publication Manual of the American Psychological Association, 7th Edition).

Acknowledgements [optional]

Any acknowledgements must be headed and in a separate paragraph, placed after the main text but before the bibliography.

Should the research have received a funding grant, then the grant provider and grant number should be detailed. If no funding was received, please state: “No financial support was received for this study.”

Competing interests

Authors are required to declare any competing interests that may be perceived as contributing to potential bias. Examples include funding for a research program or employment by, consulting for, or stocks/shares in an organization that could be financially affected by the publication of a paper, as well as patents or patent applications whose value may be affected by the publication of the paper. Authors are required to provide a statement listing any competing interests, which will be published in their article. If there are no competing interests to declare, then please state: “The authors declare no competing interests.”

Where applicable, studies must have been approved by an appropriate ethics committee, and the authors should include a statement within the article text detailing this approval, including the name of the ethics committee and reference number of the approval. The identity of the research subject(s) should be anonymized whenever possible. For research involving human subjects, informed consent to participate in the study must be obtained from participants (or their legal guardian) and added to this statement. If a study involving human subjects/tissue/data was exempt from requiring ethical approval, a confirmation statement from the relevant body should be included within the submission.

When ethnicity/gender are reported, define who determined ethnicity/gender categories, whether the options were defined by the investigator and, if so, what they were and why ethnicity/gender are considered important in the study.

Copyright and publishing rights remain with the author/s of the article/s. All articles published in the journal can be reused under the following CC license: CC BY-SA  Creative Commons Attribution-ShareAlike 4.0 International License .

Data availability

The HKS Misinformation Review requires, as a condition for publication, that all data necessary to replicate published results should be archived in the Harvard Dataverse repository, within IRB restrictions.

Please consult our data sharing policy before submission. 

A Quick Guide to Quantitative Research in the Social Sciences

(11 reviews)

Christine Davies, Carmarthen, Wales

Copyright Year: 2020

Last Update: 2021

Publisher: University of Wales Trinity Saint David

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 3/9/24

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers... read more

Comprehensiveness rating: 3 see less

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers references to other resources that can be used to deepen the knowledge. The text does not include a glossary or index. The references in the figures for each chapter are not included in the reference section. It would be helpful to include those.

Content Accuracy rating: 4

Overall, the text is accurate. For example, Figure 1 on page 6 provides a clear overview of the research process. It includes general definitions of primary and secondary research. It would be helpful to include more details to explain some of the examples before they are presented. For instance, the example on page 5 was unclear how it pertains to the literature review section.

Relevance/Longevity rating: 4

In general, the text is relevant and up-to-date. The text includes many inferences of moving from qualitative to quantitative analysis. This was surprising to me as a quantitative researcher. The author mentions that moving from a qualitative to quantitative approach should only be done when needed. As a predominantly quantitative researcher, I would not advice those interested in transitioning to using a qualitative approach that qualitative research would enhance their research—not something that should only be done if you have to.

Clarity rating: 4

The text is written in a clear manner. It would be helpful to the reader if there was a description of the tables and figures in the text before they are presented.

Consistency rating: 4

The framework for each chapter and terminology used are consistent.

Modularity rating: 4

The text is clearly divided into sections within each chapter. Overall, the chapters are a similar brief length except for the chapter on data analysis, which is much more comprehensive than others.

Organization/Structure/Flow rating: 4

The topics in the text are presented in a clear and logical order. The order of the text follows the conventional research methodology in social sciences.

Interface rating: 5

I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader.

Grammatical Errors rating: 3

There are some grammatical/typographical errors throughout. Of note, for Section 5 in the table of contents. “The” should be capitalized to start the title. In the title for Table 3, the “t” in typical should be capitalized.

Cultural Relevance rating: 4

The examples are culturally relevant. The text is geared towards learners in the UK, but examples are relevant for use in other countries (i.e., United States). I did not see any examples that may be considered culturally insensitive or offensive in any way.

I teach a course on research methods in a Bachelor of Science in Public Health program. I would consider using some of the text, particularly in the analysis chapter to supplement the current textbook in the future.

Reviewed by Finn Bell, Assistant Professor, University of Michigan, Dearborn on 1/3/24

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary. read more

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary.

Content Accuracy rating: 5

As far as I can tell, the text is accurate, error-free and unbiased.

Relevance/Longevity rating: 5

This text is up-to-date, and given the content, unlikely to become obsolete any time soon.

Clarity rating: 5

The text is very clear and accessible.

Consistency rating: 5

The text is internally consistent.

Modularity rating: 5

Given how short the text is, it seems unnecessary to divide it into smaller readings, nonetheless, it is clearly labelled such that an instructor could do so.

Organization/Structure/Flow rating: 5

The text is well-organized and brings readers through basic quantitative methods in a logical, clear fashion.

Easy to navigate. Only one table that is split between pages, but not in a way that is confusing.

Grammatical Errors rating: 5

There were no noticeable grammatical errors.

The examples in this book don't give enough information to rate this effectively.

This text is truly a very quick guide at only 26 double-spaced pages. Nonetheless, Davies packs a lot of information on the basics of quantitative research methods into this text, in an engaging way with many examples of the concepts presented. This guide is more of a brief how-to that takes readers as far as how to select statistical tests. While it would be impossible to fully learn quantitative research from such a short text, of course, this resource provides a great introduction, overview, and refresher for program evaluation courses.

Reviewed by Shari Fedorowicz, Adjunct Professor, Bridgewater State University on 12/16/22

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing... read more

Comprehensiveness rating: 5 see less

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing the reader with the ability to distinguish two terms that frequently get confused. In addition, links and outside resources are provided to deepen the understanding as an option for the reader. The use of these links, coupled with diagrams and examples make this text comprehensive.

The content is mostly accurate. Given that it is a quick guide, the author chose a good selection of which types of research designs to include. However, some are not provided. For example, correlational or cross-correlational research is omitted and is not discussed in Section 3, but is used as a statistical example in the last section.

Examples utilized were appropriate and associated with terms adding value to the learning. The tables that included differentiation between types of statistical tests along with a parametric/nonparametric table were useful and relevant.

The purpose to the text and how to use this guide book is stated clearly and is established up front. The author is also very clear regarding the skill level of the user. Adding to the clarity are the tables with terms, definitions, and examples to help the reader unpack the concepts. The content related to the terms was succinct, direct, and clear. Many times examples or figures were used to supplement the narrative.

The text is consistent throughout from contents to references. Within each section of the text, the introductory paragraph under each section provides a clear understanding regarding what will be discussed in each section. The layout is consistent for each section and easy to follow.

The contents are visible and address each section of the text. A total of seven sections, including a reference section, is in the contents. Each section is outlined by what will be discussed in the contents. In addition, within each section, a heading is provided to direct the reader to the subtopic under each section.

The text is well-organized and segues appropriately. I would have liked to have seen an introductory section giving a narrative overview of what is in each section. This would provide the reader with the ability to get a preliminary glimpse into each upcoming sections and topics that are covered.

The book was easy to navigate and well-organized. Examples are presented in one color, links in another and last, figures and tables. The visuals supplemented the reading and placed appropriately. This provides an opportunity for the reader to unpack the reading by use of visuals and examples.

No significant grammatical errors.

Cultural Relevance rating: 5

The text is not offensive or culturally insensitive. Examples were inclusive of various races, ethnicities, and backgrounds.

This quick guide is a beneficial text to assist in unpacking the learning related to quantitative statistics. I would use this book to complement my instruction and lessons, or use this book as a main text with supplemental statistical problems and formulas. References to statistical programs were appropriate and were useful. The text did exactly what was stated up front in that it is a direct guide to quantitative statistics. It is well-written and to the point with content areas easy to locate by topic.

Reviewed by Sarah Capello, Assistant Professor, Radford University on 1/18/22

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text. read more

Comprehensiveness rating: 4 see less

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text.

The content is mostly accurate. I would have preferred a few nuances to be hashed out a bit further to avoid potential reader confusion or misunderstanding of the concepts presented.

The content is current; however, some of the references cited in the text are outdated. Newer editions of those texts exist.

The text is very accessible and readable for a variety of audiences. Key terms are well-defined.

There are no content discrepancies within the text. The author even uses similarly shaped graphics for recurring purposes throughout the text (e.g., arrow call outs for further reading, rectangle call outs for examples).

The content is chunked nicely by topics and sections. If it were used for a course, it would be easy to assign different sections of the text for homework, etc. without confusing the reader if the instructor chose to present the content in a different order.

The author follows the structure of the research process. The organization of the text is easy to follow and comprehend.

All of the supplementary images (e.g., tables and figures) were beneficial to the reader and enhanced the text.

There are no significant grammatical errors.

I did not find any culturally offensive or insensitive references in the text.

This text does the difficult job of introducing the complicated concepts and processes of quantitative research in a quick and easy reference guide fairly well. I would not depend solely on this text to teach students about quantitative research, but it could be a good jumping off point for those who have no prior knowledge on this subject or those who need a gentle introduction before diving in to more advanced and complex readings of quantitative research methods.

Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 12/9/21

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of... read more

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of thought. There is no glossary but, for a guide of this length, a glossary does not seem like it would enhance the guide significantly.

The content is relatively accurate. Expanding the content a bit more or explaining that the methods and designs presented are not entirely inclusive would help. As there are different schools of thought regarding what should/should not be included in terms of these designs and methods, simply bringing attention to that and explaining a bit more would help.

Relevance/Longevity rating: 3

This content needs to be updated. Most of the sources cited are seven or more years old. Even more, it would be helpful to see more currently relevant examples. Some of the source authors such as Andy Field provide very interesting and dynamic instruction in general, but they have much more current information available.

The language used is clear and appropriate. Unnecessary jargon is not used. The intent is clear- to communicate simply in a straightforward manner.

The guide seems to be internally consistent in terms of terminology and framework. There do not seem to be issues in this area. Terminology is internally consistent.

For a guide of this length, the author structured this logically into sections. This guide could be adopted in whole or by section with limited modifications. Courses with fewer than seven modules could also logically group some of the sections.

This guide does present with logical organization. The topics presented are conceptually sequenced in a manner that helps learners build logically on prior conceptualization. This also provides a simple conceptual framework for instructors to guide learners through the process.

Interface rating: 4

The visuals themselves are simple, but they are clear and understandable without distracting the learner. The purpose is clear- that of learning rather than visuals for the sake of visuals. Likewise, navigation is clear and without issues beyond a broken link (the last source noted in the references).

This guide seems to be free of grammatical errors.

It would be interesting to see more cultural integration in a guide of this nature, but the guide is not culturally insensitive or offensive in any way. The language used seems to be consistent with APA's guidelines for unbiased language.

Reviewed by Heng Yu-Ku, Professor, University of Northern Colorado on 5/13/21

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive... read more

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive research study as an Appendix after section 7 (page 26) to help readers comprehend information better.

For the most part, the content is accurate and unbiased. However, the author only includes four types of research designs used on the social sciences that contain quantitative elements: 1. Mixed method, 2) Case study, 3) Quasi-experiment, and 3) Action research. I wonder why the correlational research is not included as another type of quantitative research design as it has been introduced and emphasized in section 6 by the author.

I believe the content is up-to-date and that necessary updates will be relatively easy and straightforward to implement.

The text is easy to read and provides adequate context for any technical terminology used. However, the author could provide more detailed information about estimating the minimum sample size but not just refer the readers to use the online sample calculators at a different website.

The text is internally consistent in terms of terminology and framework. The author provides the right amount of information with additional information or resources for the readers.

The text includes seven sections. Therefore, it is easier for the instructor to allocate or divide the content into different weeks of instruction within the course.

Yes, the topics in the text are presented in a logical and clear fashion. The author provides clear and precise terminologies, summarizes important content in Table or Figure forms, and offers examples in each section for readers to check their understanding.

The interface of the book is consistent and clear, and all the images and charts provided in the book are appropriate. However, I did encounter some navigation problems as a couple of links are not working or requires permission to access those (pages 10 and 27).

No grammatical errors were found.

No culturally incentive or offensive in its language and the examples provided were found.

As the book title stated, this book provides “A Quick Guide to Quantitative Research in Social Science. It offers easy-to-read information and introduces the readers to the research process, such as research questions, research paradigms, research process, research designs, research methods, data collection, data analysis, and data discussion. However, some links are not working or need permissions to access them (pages 10 and 27).

Reviewed by Hsiao-Chin Kuo, Assistant Professor, Northeastern Illinois University on 4/26/21, updated 4/28/21

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and... read more

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and process, discusses methods, data collection and analysis, and ends with writing a research report. It also identifies its target readers/users as those begins to explore quantitative research. It would be helpful to include more examples for readers/users who are new to quantitative research.

Its content is mostly accurate and no bias given its nature as a quick guide. Yet, it is also quite simplified, such as its explanations of mixed methods, case study, quasi-experimental research, and action research. It provides resources for extended reading, yet more recent works will be helpful.

The book is relevant given its nature as a quick guide. It would be helpful to provide more recent works in its resources for extended reading, such as the section for Survey Research (p. 12). It would also be helpful to include more information to introduce common tools and software for statistical analysis.

The book is written with clear and understandable language. Important terms and concepts are presented with plain explanations and examples. Figures and tables are also presented to support its clarity. For example, Table 4 (p. 20) gives an easy-to-follow overview of different statistical tests.

The framework is very consistent with key points, further explanations, examples, and resources for extended reading. The sample studies are presented following the layout of the content, such as research questions, design and methods, and analysis. These examples help reinforce readers' understanding of these common research elements.

The book is divided into seven chapters. Each chapter clearly discusses an aspect of quantitative research. It can be easily divided into modules for a class or for a theme in a research method class. Chapters are short and provides additional resources for extended reading.

The topics in the chapters are presented in a logical and clear structure. It is easy to follow to a degree. Though, it would be also helpful to include the chapter number and title in the header next to its page number.

The text is easy to navigate. Most of the figures and tables are displayed clearly. Yet, there are several sections with empty space that is a bit confusing in the beginning. Again, it can be helpful to include the chapter number/title next to its page number.

Grammatical Errors rating: 4

No major grammatical errors were found.

There are no cultural insensitivities noted.

Given the nature and purpose of this book, as a quick guide, it provides readers a quick reference for important concepts and terms related to quantitative research. Because this book is quite short (27 pages), it can be used as an overview/preview about quantitative research. Teacher's facilitation/input and extended readings will be needed for a deeper learning and discussion about aspects of quantitative research.

Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 1/6/21

It covers the most important topics such as research progress, resources, measurement, and analysis of the data. read more

It covers the most important topics such as research progress, resources, measurement, and analysis of the data.

The book accurately describes the types of research methods such as mixed-method, quasi-experiment, and case study. It talks about the research proposal and key differences between statistical analyses as well.

The book pinpointed the significance of running a quantitative research method and its relevance to the field of social science.

The book clearly tells us the differences between types of quantitative methods and the steps of running quantitative research for students.

The book is consistent in terms of terminologies such as research methods or types of statistical analysis.

It addresses the headlines and subheadlines very well and each subheading should be necessary for readers.

The book was organized very well to illustrate the topic of quantitative methods in the field of social science.

The pictures within the book could be further developed to describe the key concepts vividly.

The textbook contains no grammatical errors.

It is not culturally offensive in any way.

Overall, this is a simple and quick guide for this important topic. It should be valuable for undergraduate students who would like to learn more about research methods.

Reviewed by Pierre Lu, Associate Professor, University of Texas Rio Grande Valley on 11/20/20

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas. read more

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas.

Mostly accurate content.

As a quick guide, content is highly relevant.

Succinct and clear.

Internally, the text is consistent in terms of terminology used.

The text is easily and readily divisible into smaller sections that can be used as assignments.

I like that there are examples throughout the book.

Easy to read. No interface/ navigation problems.

No grammatical errors detected.

I am not aware of the culturally insensitive description. After all, this is a methodology book.

I think the book has potential to be adopted as a foundation for quantitative research courses, or as a review in the first weeks in advanced quantitative course.

Reviewed by Sarah Fischer, Assistant Professor, Marymount University on 7/31/20

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable). read more

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable).

Content Accuracy rating: 1

Contains VERY significant errors, such as saying that one can "accept" a hypothesis. (One of the key aspect of hypothesis testing is that one either rejects or fails to reject a hypothesis, but NEVER accepts a hypothesis.)

Very relevant to those experiencing the research process for the first time. However, it is written by someone working in the natural sciences but is a text for social sciences. This does not explain the errors, but does explain why sometimes the author assumes things about the readers ("hail from more subjectivist territory") that are likely not true.

Clarity rating: 3

Some statistical terminology not explained clearly (or accurately), although the author has made attempts to do both.

Very consistently laid out.

Chapters are very short yet also point readers to outside texts for additional information. Easy to follow.

Generally logically organized.

Easy to navigate, images clear. The additional sources included need to linked to.

Minor grammatical and usage errors throughout the text.

Makes efforts to be inclusive.

The idea of this book is strong--short guides like this are needed. However, this book would likely be strengthened by a revision to reduce inaccuracies and improve the definitions and technical explanations of statistical concepts. Since the book is specifically aimed at the social sciences, it would also improve the text to have more examples that are based in the social sciences (rather than the health sciences or the arts).

Reviewed by Michelle Page, Assistant Professor, Worcester State University on 5/30/20

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new... read more

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new researcher would not be able to use this as a stand alone guide for quantitative pursuits without having a supplemental text that explains the steps in the process more comprehensively. The introduction does provide this caveat.

Content Accuracy rating: 3

There are no biases or errors that could be distinguished; however, it’s simplicity in content, although accurate for an outline of process, may lack a conveyance of the deeper meanings behind the specific processes explained about qualitative research.

The content is outlined in traditional format to highlight quantitative considerations for formatting research foundational pieces. The resources/references used to point the reader to literature sources can be easily updated with future editions.

The jargon in the text is simple to follow and provides adequate context for its purpose. It is simplified for its intention as a guide which is appropriate.

Each section of the text follows a consistent flow. Explanation of the research content or concept is defined and then a connection to literature is provided to expand the readers understanding of the section’s content. Terminology is consistent with the qualitative process.

As an “outline” and guide, this text can be used to quickly identify the critical parts of the quantitative process. Although each section does not provide deeper content for meaningful use as a stand alone text, it’s utility would be excellent as a reference for a course and can be used as an content guide for specific research courses.

The text’s outline and content are aligned and are in a logical flow in terms of the research considerations for quantitative research.

The only issue that the format was not able to provide was linkable articles. These would have to be cut and pasted into a browser. Functional clickable links in a text are very successful at leading the reader to the supplemental material.

No grammatical errors were noted.

This is a very good outline “guide” to help a new or student researcher to demystify the quantitative process. A successful outline of any process helps to guide work in a logical and systematic way. I think this simple guide is a great adjunct to more substantial research context.

Table of Contents

• Section 1: What will this resource do for you?
• Section 2: Why are you thinking about numbers? A discussion of the research question and paradigms.
• Section 3: An overview of the Research Process and Research Designs
• Section 4: Quantitative Research Methods
• Section 5: the data obtained from quantitative research
• Section 6: Analysis of data
• Section 7: Discussing your Results

Ancillary Material

About the book.

This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real help.

The booklet was amended in 2022 to take into account previous review comments.  

About the Contributors

Christine Davies , Ph.D

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100+ Quantitative Research Topics For Students

Quantitative research is a research strategy focusing on quantified data collection and analysis processes. This research strategy emphasizes testing theories on various subjects. It also includes collecting and analyzing non-numerical data.

Quantitative research is a common approach in the natural and social sciences , like marketing, business, sociology, chemistry, biology, economics, and psychology. So, if you are fond of statistics and figures, a quantitative research title would be an excellent option for your research proposal or project.

How to Get a Title of Quantitative Research

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Finding a great title is the key to writing a great quantitative research proposal or paper. A title for quantitative research prepares you for success, failure, or mediocre grades. This post features examples of quantitative research titles for all students.

Putting together a research title and quantitative research design is not as easy as some students assume. So, an example topic of quantitative research can help you craft your own. However, even with the examples, you may need some guidelines for personalizing your research project or proposal topics.

So, here are some tips for getting a title for quantitative research:

• Consider your area of studies
• Look out for relevant subjects in the area
• Expert advice may come in handy
• Check out some sample quantitative research titles

Making a quantitative research title is easy if you know the qualities of a good title in quantitative research. Reading about how to make a quantitative research title may not help as much as looking at some samples. Looking at a quantitative research example title will give you an idea of where to start.

However, let’s look at some tips for how to make a quantitative research title:

• The title should seem interesting to readers
• Ensure that the title represents the content of the research paper
• Reflect on the tone of the writing in the title
• The title should contain important keywords in your chosen subject to help readers find your paper
• The title should not be too lengthy
• It should be grammatically correct and creative
• It must generate curiosity

An excellent quantitative title should be clear, which implies that it should effectively explain the paper and what readers can expect. A research title for quantitative research is the gateway to your article or proposal. So, it should be well thought out. Additionally, it should give you room for extensive topic research.

A sample of quantitative research titles will give you an idea of what a good title for quantitative research looks like. Here are some examples:

• What is the correlation between inflation rates and unemployment rates?
• Has climate adaptation influenced the mitigation of funds allocation?
• Job satisfaction and employee turnover: What is the link?
• A look at the relationship between poor households and the development of entrepreneurship skills
• Urbanization and economic growth: What is the link between these elements?
• Does education achievement influence people’s economic status?
• What is the impact of solar electricity on the wholesale energy market?
• Debt accumulation and retirement: What is the relationship between these concepts?
• Can people with psychiatric disorders develop independent living skills?
• Children’s nutrition and its impact on cognitive development

Quantitative research applies to various subjects in the natural and social sciences. Therefore, depending on your intended subject, you have numerous options. Below are some good quantitative research topics for students:

• The difference between the colorific intake of men and women in your country
• Top strategies used to measure customer satisfaction and how they work
• Black Friday sales: are they profitable?
• The correlation between estimated target market and practical competitive risk assignment
• Are smartphones making us brighter or dumber?
• Nuclear families Vs. Joint families: Is there a difference?
• What will society look like in the absence of organized religion?
• A comparison between carbohydrate weight loss benefits and high carbohydrate diets?
• How does emotional stability influence your overall well-being?
• The extent of the impact of technology in the communications sector

Creativity is the key to creating a good research topic in quantitative research. Find a good quantitative research topic below:

• How much exercise is good for lasting physical well-being?
• A comparison of the nutritional therapy uses and contemporary medical approaches
• Does sugar intake have a direct impact on diabetes diagnosis?
• Education attainment: Does it influence crime rates in society?
• Is there an actual link between obesity and cancer rates?
• Do kids with siblings have better social skills than those without?
• Computer games and their impact on the young generation
• Has social media marketing taken over conventional marketing strategies?
• The impact of technology development on human relationships and communication
• What is the link between drug addiction and age?

Need more quantitative research title examples to inspire you? Here are some quantitative research title examples to look at:

• Habitation fragmentation and biodiversity loss: What is the link?
• Radiation has affected biodiversity: Assessing its effects
• An assessment of the impact of the CORONA virus on global population growth
• Is the pandemic truly over, or have human bodies built resistance against the virus?
• The ozone hole and its impact on the environment
• The greenhouse gas effect: What is it and how has it impacted the atmosphere
• GMO crops: are they good or bad for your health?
• Is there a direct link between education quality and job attainment?
• How have education systems changed from traditional to modern times?
• The good and bad impacts of technology on education qualities

Your examiner will give you excellent grades if you come up with a unique title and outstanding content. Here are some quantitative research examples titles.

• Online classes: are they helpful or not?
• What changes has the global CORONA pandemic had on the population growth curve?
• Daily habits influenced by the global pandemic
• An analysis of the impact of culture on people’s personalities
• How has feminism influenced the education system’s approach to the girl child’s education?
• Academic competition: what are its benefits and downsides for students?
• Is there a link between education and student integrity?
• An analysis of how the education sector can influence a country’s economy
• An overview of the link between crime rates and concern for crime
• Is there a link between education and obesity?

Research title example quantitative topics when well-thought guarantees a paper that is a good read. Look at the examples below to get started.

• What are the impacts of online games on students?
• Sex education in schools: how important is it?
• Should schools be teaching about safe sex in their sex education classes?
• The correlation between extreme parent interference on student academic performance
• Is there a real link between academic marks and intelligence?
• Teacher feedback: How necessary is it, and how does it help students?
• An analysis of modern education systems and their impact on student performance
• An overview of the link between academic performance/marks and intelligence
• Are grading systems helpful or harmful to students?
• What was the impact of the pandemic on students?

Irrespective of the course you take, here are some titles that can fit diverse subjects pretty well. Here are some creative quantitative research title ideas:

• A look at the pre-corona and post-corona economy
• How are conventional retail businesses fairing against eCommerce sites like Amazon and Shopify?
• An evaluation of mortality rates of heart attacks
• Effective treatments for cardiovascular issues and their prevention
• A comparison of the effectiveness of home care and nursing home care
• Strategies for managing effective dissemination of information to modern students
• How does educational discrimination influence students’ futures?
• The impacts of unfavorable classroom environment and bullying on students and teachers
• An overview of the implementation of STEM education to K-12 students
• How effective is digital learning?

If your paper addresses a problem, you must present facts that solve the question or tell more about the question. Here are examples of quantitative research titles that will inspire you.

• An elaborate study of the influence of telemedicine in healthcare practices
• How has scientific innovation influenced the defense or military system?
• The link between technology and people’s mental health
• Has social media helped create awareness or worsened people’s mental health?
• How do engineers promote green technology?
• How can engineers raise sustainability in building and structural infrastructures?
• An analysis of how decision-making is dependent on someone’s sub-conscious
• A comprehensive study of ADHD and its impact on students’ capabilities
• The impact of racism on people’s mental health and overall wellbeing
• How has the current surge in social activism helped shape people’s relationships?

Are you looking for an example of a quantitative research title? These ten examples below will get you started.

• The prevalence of nonverbal communication in social control and people’s interactions
• The impacts of stress on people’s behavior in society
• A study of the connection between capital structures and corporate strategies
• How do changes in credit ratings impact equality returns?
• A quantitative analysis of the effect of bond rating changes on stock prices
• The impact of semantics on web technology
• An analysis of persuasion, propaganda, and marketing impact on individuals
• The dominant-firm model: what is it, and how does it apply to your country’s retail sector?
• The role of income inequality in economy growth
• An examination of juvenile delinquents’ treatment in your country

Excellent Topics For Quantitative Research

Here are some titles for quantitative research you should consider:

• Does studying mathematics help implement data safety for businesses
• How are art-related subjects interdependent with mathematics?
• How do eco-friendly practices in the hospitality industry influence tourism rates?
• A deep insight into how people view eco-tourisms
• Religion vs. hospitality: Details on their correlation
• Has your country’s tourist sector revived after the pandemic?
• How effective is non-verbal communication in conveying emotions?
• Are there similarities between the English and French vocabulary?
• How do politicians use persuasive language in political speeches?
• The correlation between popular culture and translation

Here are some quantitative research titles examples for your consideration:

• How do world leaders use language to change the emotional climate in their nations?
• Extensive research on how linguistics cultivate political buzzwords
• The impact of globalization on the global tourism sector
• An analysis of the effects of the pandemic on the worldwide hospitality sector
• The influence of social media platforms on people’s choice of tourism destinations
• Educational tourism: What is it and what you should know about it
• Why do college students experience math anxiety?
• Is math anxiety a phenomenon?
• A guide on effective ways to fight cultural bias in modern society
• Creative ways to solve the overpopulation issue

An example of quantitative research topics for 12 th -grade students will come in handy if you want to score a good grade. Here are some of the best ones:

• The link between global warming and climate change
• What is the greenhouse gas impact on biodiversity and the atmosphere
• Has the internet successfully influenced literacy rates in society
• The value and downsides of competition for students
• A comparison of the education system in first-world and third-world countries
• The impact of alcohol addiction on the younger generation
• How has social media influenced human relationships?
• Has education helped boost feminism among men and women?
• Are computers in classrooms beneficial or detrimental to students?
• How has social media improved bullying rates among teenagers?

High school students can apply research titles on social issues  or other elements, depending on the subject. Let’s look at some quantitative topics for students:

• What is the right age to introduce sex education for students
• Can extreme punishment help reduce alcohol consumption among teenagers?
• Should the government increase the age of sexual consent?
• The link between globalization and the local economy collapses
• How are global companies influencing local economies?

There are numerous possible quantitative research topics you can write about. Here are some great quantitative research topics examples:

• The correlation between video games and crime rates
• Do college studies impact future job satisfaction?
• What can the education sector do to encourage more college enrollment?
• The impact of education on self-esteem
• The relationship between income and occupation

You can find inspiration for your research topic from trending affairs on social media or in the news. Such topics will make your research enticing. Find a trending topic for quantitative research example from the list below:

• How the country’s economy is fairing after the pandemic
• An analysis of the riots by women in Iran and what the women gain to achieve
• Is the current US government living up to the voter’s expectations?
• How is the war in Ukraine affecting the global economy?
• Can social media riots affect political decisions?

A proposal is a paper you write proposing the subject you would like to cover for your research and the research techniques you will apply. If the proposal is approved, it turns to your research topic. Here are some quantitative titles you should consider for your research proposal:

• Military support and economic development: What is the impact in developing nations?
• How does gun ownership influence crime rates in developed countries?
• How can the US government reduce gun violence without influencing people’s rights?
• What is the link between school prestige and academic standards?
• Is there a scientific link between abortion and the definition of viability?

You can never have too many sample titles. The samples allow you to find a unique title you’re your research or proposal. Find a sample quantitative research title here:

• Does weight loss indicate good or poor health?
• Should schools do away with grading systems?
• The impact of culture on student interactions and personalities
• How can parents successfully protect their kids from the dangers of the internet?
• Is the US education system better or worse than Europe’s?

If you’re a business major, then you must choose a research title quantitative about business. Let’s look at some research title examples quantitative in business:

• Creating shareholder value in business: How important is it?
• The changes in credit ratings and their impact on equity returns
• The importance of data privacy laws in business operations
• How do businesses benefit from e-waste and carbon footprint reduction?
• Organizational culture in business: what is its importance?

We Are A Call Away

Interesting, creative, unique, and easy quantitative research topics allow you to explain your paper and make research easy. Therefore, you should not take choosing a research paper or proposal topic lightly. With your topic ready, reach out to us today for excellent research paper writing services .

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6 Important Tips on Writing a Research Paper Title

When you are searching for a research study on a particular topic, you probably notice that articles with interesting, descriptive research titles draw you in. By contrast, research paper titles that are not descriptive are usually passed over, even though you may write a good research paper with interesting contents. This shows the importance of coming up with a good title for your research paper when drafting your own manuscript.

Importance of a Research Title

The research title plays a crucial role in the research process, and its importance can be summarized as follows:

Why do Research Titles Matter?

Before we look at how to title a research paper, let’s look at a research title example that illustrates why a good research paper should have a strong title.

Imagine that you are researching meditation and nursing, and you want to find out if any studies have shown that meditation makes nurses better communicators.  You conduct a keyword search using the keywords “nursing”, “communication”, and “meditation.” You come up with results that have the following titles:

• Benefits of Meditation for the Nursing Profession: A Quantitative Investigation
• Why Mindful Nurses Make the Best Communicators
• Meditation Gurus
• Nurses on the Move: A Quantitative Report on How Meditation Can Improve Nurse Performance

All four of these research paper titles may describe very similar studies—they could even be titles for the same study! As you can see, they give very different impressions.

• Title 1 describes the topic and the method of the study but is not particularly catchy.
• Title 2 partly describes the topic, but does not give any information about the method of the study—it could simply be a theoretical or opinion piece.
• Title 3 is somewhat catchier but gives almost no information at all about the article.
• Title 4 begins with a catchy main title and is followed by a subtitle that gives information about the content and method of the study.

As we will see, Title 4 has all the characteristics of a good research title.

Characteristics of a Good Research Title

According to rhetoric scholars Hairston and Keene, making a good title for a paper involves ensuring that the title of the research accomplishes four goals as mentioned below:

• It should predict the content of the research paper .
• It should be interesting to the reader .
• It should reflect the tone of the writing .
• It should contain important keywords that will make it easier to be located during a keyword search.

Let’s return to the examples in the previous section to see how to make a research title.

As you can see in the table above, only one of the four example titles fulfills all of the criteria of a suitable research paper title.

Related: You’ve chosen your study topic, but having trouble deciding where to publish it? Here’s a comprehensive course to help you identify the right journal .

Tips for Writing an Effective Research Paper Title

When writing a research title, you can use the four criteria listed above as a guide. Here are a few other tips you can use to make sure your title will be part of the recipe for an effective research paper :

• Make sure your research title describes (a) the topic, (b) the method, (c) the sample, and (d) the results of your study. You can use the following formula:

[ Result ]: A [ method ] study of [ topic ] among [ sample ] Example : Meditation makes nurses perform better: a qualitative study of mindfulness meditation among German nursing students

• Avoid unnecessary words and jargons. Keep the title statement as concise as possible. You want a title that will be comprehensible even to people who are not experts in your field. Check our article for a detailed list of things to avoid when writing an effective research title .
• Make sure your title is between 5 and 15 words in length.
• If you are writing a title for a university assignment or for a particular academic journal, verify that your title conforms to the standards and requirements for that outlet. For example, many journals require that titles fall under a character limit, including spaces. Many universities require that titles take a very specific form, limiting your creativity.
• Use a descriptive phrase to convey the purpose of your research efficiently.
• Most importantly, use critical keywords in the title to increase the discoverability of your article.

Resources for Further Reading

In addition to the tips above, there are many resources online that you can use to help write your research title. Here is a list of links that you may find useful as you work on creating an excellent research title:

• The University of Southern California has a guide specific to social science research papers: http://libguides.usc.edu/writingguide/title
• The Journal of European Psychology Students has a blog article focusing on APA-compliant research paper titles: http://blog.efpsa.org/2012/09/01/how-to-write-a-good-title-for-journal-articles/
• This article by Kristen Hamlin contains a step-by-step approach to writing titles: http://classroom.synonym.com/choose-title-research-paper-4332.html

Are there any tips or tricks you find useful in crafting research titles? Which tip did you find most useful in this article? Leave a comment to let us know!

• Hairston, M., & Keene, M. 2003. Successful writing . 5th ed. New York: Norton.
• University of Southern California. 2017. Organizing your social sciences research paper: choosing a title . [Online] Available at: http://libguides.usc.edu/writingguide/title

Thank you so much:) Have a nice day!

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Thank you for the excellent article and tips for creating a research work, because I always forget about such an essential element as the keywords when forming topics. In particular, I have found a rapid help with the formation of informative and sound titles that also conforms to the standards and requirements.

I am doing a research work on sales girls or shop girls using qualititative method. Basicly I am from Pakistan and writing on the scenario of mycountry. I am really confused about my research title can you kindly give some suggestions and give me an approperaite tilte

Hi Zubair, Thank you for your question. However, the information you have provided is insufficient for drafting an appropriate title. Information on what exactly you intend to study would be needed in order to draft a meaningful title. Meanwhile, you can try drafting your own title after going through the following articles our website: https://www.enago.com/academy/top-10-tips-on-choosing-an-attractive-research-title/ , https://www.enago.com/academy/writing-a-good-research-title-things-to-avoid/ , https://www.enago.com/academy/write-irresistible-research-paper-title/ We would be happy to give you feedback and suggest changes if required. Did you get a chance to install our free Mobile App? https://www.enago.com/academy/mobile-app/ . Make sure you subscribe to our weekly newsletter https://www.enago.com/academy/subscribe-now/ .

thanks for helping me like this!!

Thank you for this. It helped me improve my research title. I just want to verify to you the title I have just made. “Ensuring the safety: A Quantitative Study of Radio Frequency Identification system among the selected students of ( school’s name ).

(I need your reply asap coz we will be doing the chap. 1 tomorrow. Thank u in advance. 🙂 )

I am actually doing a research paper title. I want to know more further in doing research title. Can you give me some tips on doing a research paper?

Hi Joan, Thank you for your question. We are glad to know that you found our resources useful. Your feedback is very valuable to us. You can try drafting your own title after going through the following articles on our website: https://www.enago.com/academy/top-10-tips-on-choosing-an-attractive-research-title/ , https://www.enago.com/academy/writing-a-good-research-title-things-to-avoid/ , https://www.enago.com/academy/write-irresistible-research-paper-title/

We would be happy to give you feedback and suggest changes if required. Did you get a chance to install our free Mobile App? https://www.enago.com/academy/mobile-app/ . Make sure you subscribe to our weekly newsletter https://www.enago.com/academy/subscribe-now/ .

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I need help. I need a research title for my study about early mobilization of the mechanically ventilated patients in the ICU. Any suggestions would be highly appreciated.

Thank you for posting your query on the website. When writing manuscripts, too many scholars neglect the research title. This phrase, along with the abstract, is what people will mostly see and read online. Title research of publications shows that the research paper title does matter a lot. Both bibliometrics and altmetrics tracking of citations are now, for better or worse, used to gauge a paper’s “success” for its author(s) and the journal publishing it. Interesting research topics coupled with good or clever yet accurate research titles can draw more attention to your work from peers and the public alike. You can check through the following search results for titles on similar topics: https://www.google.com/search?q=early+mobilization+of+the+mechanically+ventilated+patients+in+the+icu&rlz=1C1GCEU_enIN907IN907&oq=&aqs=chrome.0.69i59.4920093j0j7&sourceid=chrome&ie=UTF-8 .

We hope this would be helpful in drafting an attractive title for your research paper.

Please let us know in case of any other queries.

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How to Make a Research Paper Title with Examples

What is a research paper title and why does it matter?

A research paper title summarizes the aim and purpose of your research study. Making a title for your research is one of the most important decisions when writing an article to publish in journals. The research title is the first thing that journal editors and reviewers see when they look at your paper and the only piece of information that fellow researchers will see in a database or search engine query. Good titles that are concise and contain all the relevant terms have been shown to increase citation counts and Altmetric scores .

Therefore, when you title research work, make sure it captures all of the relevant aspects of your study, including the specific topic and problem being investigated. It also should present these elements in a way that is accessible and will captivate readers. Follow these steps to learn how to make a good research title for your work.

How to Make a Research Paper Title in 5 Steps

You might wonder how you are supposed to pick a title from all the content that your manuscript contains—how are you supposed to choose? What will make your research paper title come up in search engines and what will make the people in your field read it? 

In a nutshell, your research title should accurately capture what you have done, it should sound interesting to the people who work on the same or a similar topic, and it should contain the important title keywords that other researchers use when looking for literature in databases. To make the title writing process as simple as possible, we have broken it down into 5 simple steps.

Step 1: Answer some key questions about your research paper

What does your paper seek to answer and what does it accomplish? Try to answer these questions as briefly as possible. You can create these questions by going through each section of your paper and finding the MOST relevant information to make a research title.

Step 2: Identify research study keywords

Now that you have answers to your research questions, find the most important parts of these responses and make these your study keywords. Note that you should only choose the most important terms for your keywords–journals usually request anywhere from 3 to 8 keywords maximum.

Step 3: Research title writing: use these keywords

“We employed a case study of 60 liver transplant patients around the US aged 20-50 years to assess how waiting list volume affects the outcomes of liver transplantation in patients; results indicate a positive correlation between increased waiting list volume and negative prognosis after the transplant procedure.”

The sentence above is clearly much too long for a research paper title. This is why you will trim and polish your title in the next two steps.

Step 4: Create a working research paper title

To create a working title, remove elements that make it a complete “sentence” but keep everything that is important to what the study is about. Delete all unnecessary and redundant words that are not central to the study or that researchers would most likely not use in a database search.

“ We employed a case study of 60 liver transplant patients around the US aged 20-50 years to assess how the waiting list volume affects the outcome of liver transplantation in patients ; results indicate a positive correlation between increased waiting list volume and a negative prognosis after transplant procedure ”

Now shift some words around for proper syntax and rephrase it a bit to shorten the length and make it leaner and more natural. What you are left with is:

“A case study of 60 liver transplant patients around the US aged 20-50 years assessing the impact of waiting list volume on outcome of transplantation and showing a positive correlation between increased waiting list volume and a negative prognosis” (Word Count: 38)

This text is getting closer to what we want in a research title, which is just the most important information. But note that the word count for this working title is still 38 words, whereas the average length of published journal article titles is 16 words or fewer. Therefore, we should eliminate some words and phrases that are not essential to this title.

Step 5: Remove any nonessential words and phrases from your title

Because the number of patients studied and the exact outcome are not the most essential parts of this paper, remove these elements first:

 “A case study of 60 liver transplant patients around the US aged 20-50 years assessing the impact of waiting list volume on outcomes of transplantation and showing a positive correlation between increased waiting list volume and a negative prognosis” (Word Count: 19)

In addition, the methods used in a study are not usually the most searched-for keywords in databases and represent additional details that you may want to remove to make your title leaner. So what is left is:

“Assessing the impact of waiting list volume on outcome and prognosis in liver transplantation patients” (Word Count: 15)

In this final version of the title, one can immediately recognize the subject and what objectives the study aims to achieve. Note that the most important terms appear at the beginning and end of the title: “Assessing,” which is the main action of the study, is placed at the beginning; and “liver transplantation patients,” the specific subject of the study, is placed at the end.

This will aid significantly in your research paper title being found in search engines and database queries, which means that a lot more researchers will be able to locate your article once it is published. In fact, a 2014 review of more than 150,000 papers submitted to the UK’s Research Excellence Framework (REF) database found the style of a paper’s title impacted the number of citations it would typically receive. In most disciplines, articles with shorter, more concise titles yielded more citations.

Adding a Research Paper Subtitle

If your title might require a subtitle to provide more immediate details about your methodology or sample, you can do this by adding this information after a colon:

“ : a case study of US adult patients ages 20-25”

If we abide strictly by our word count rule this may not be necessary or recommended. But every journal has its own standard formatting and style guidelines for research paper titles, so it is a good idea to be aware of the specific journal author instructions , not just when you write the manuscript but also to decide how to create a good title for it.

Research Paper Title Examples

The title examples in the following table illustrate how a title can be interesting but incomplete, complete by uninteresting, complete and interesting but too informal in tone, or some other combination of these. A good research paper title should meet all the requirements in the four columns below.

Tips on Formulating a Good Research Paper Title

In addition to the steps given above, there are a few other important things you want to keep in mind when it comes to how to write a research paper title, regarding formatting, word count, and content:

• Write the title after you’ve written your paper and abstract
• Include all of the essential terms in your paper
• Keep it short and to the point (~16 words or fewer)
• Avoid unnecessary jargon and abbreviations
• Use keywords that capture the content of your paper
• Never include a period at the end—your title is NOT a sentence

Research Paper Writing Resources

We hope this article has been helpful in teaching you how to craft your research paper title. But you might still want to dig deeper into different journal title formats and categories that might be more suitable for specific article types or need help with writing a cover letter for your manuscript submission.

In addition to getting English proofreading services , including paper editing services , before submission to journals, be sure to visit our academic resources papers. Here you can find dozens of articles on manuscript writing, from drafting an outline to finding a target journal to submit to.

Quantitative and Qualitative Research

• I NEED TO . . .

What is Quantitative Research?

• What is Qualitative Research?
• Quantitative vs Qualitative
• Step 1: Accessing CINAHL
• Step 2: Create a Keyword Search
• Step 3: Create a Subject Heading Search
• Step 4: Repeat Steps 1-3 for Second Concept
• Step 5: Repeat Steps 1-3 for Quantitative Terms
• Step 6: Combining All Searches
• Step 7: Adding Limiters
• Step 8: Save Your Search!
• What Kind of Article is This?
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Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is  imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014).  The SAGE encyclopedia of action research  (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017).  The SAGE encyclopedia of communication research methods  (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design?  What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used.  You will need to know how to decipher which design type is used.  The following video will help you determine the quantitative design type.

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• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

How to structure quantitative research questions

There is no "one best way" to structure a quantitative research question. However, to create a well-structured quantitative research question, we recommend an approach that is based on four steps : (1) Choosing the type of quantitative research question you are trying to create (i.e., descriptive, comparative or relationship-based); (2) Identifying the different types of variables you are trying to measure, manipulate and/or control, as well as any groups you may be interested in; (3) Selecting the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved; and (4) Writing out the problem or issues you are trying to address in the form of a complete research question. In this article, we discuss each of these four steps , as well as providing examples for the three types of quantitative research question you may want to create: descriptive , comparative and relationship-based research questions .

• STEP ONE: Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create
• STEP TWO: Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in
• STEP THREE: Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved
• STEP FOUR: Write out the problem or issues you are trying to address in the form of a complete research question

STEP ONE Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create

The type of quantitative research question that you use in your dissertation (i.e., descriptive , comparative and/or relationship-based ) needs to be reflected in the way that you write out the research question; that is, the word choice and phrasing that you use when constructing a research question tells the reader whether it is a descriptive, comparative or relationship-based research question. Therefore, in order to know how to structure your quantitative research question, you need to start by selecting the type of quantitative research question you are trying to create: descriptive, comparative and/or relationship-based.

STEP TWO Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in

Whether you are trying to create a descriptive, comparative or relationship-based research question, you will need to identify the different types of variable that you are trying to measure , manipulate and/or control . If you are unfamiliar with the different types of variable that may be part of your study, the article, Types of variable , should get you up to speed. It explains the two main types of variables: categorical variables (i.e., nominal , dichotomous and ordinal variables) and continuous variables (i.e., interval and ratio variables). It also explains the difference between independent and dependent variables , which you need to understand to create quantitative research questions.

To provide a brief explanation; a variable is not only something that you measure , but also something that you can manipulate and control for. In most undergraduate and master's level dissertations, you are only likely to measure and manipulate variables. You are unlikely to carry out research that requires you to control for variables, although some supervisors will expect this additional level of complexity. If you plan to only create descriptive research questions , you may simply have a number of dependent variables that you need to measure. However, where you plan to create comparative and/or relationship-based research questions , you will deal with both dependent and independent variables . An independent variable (sometimes called an experimental or predictor variable ) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable (sometimes called an outcome variable ). For example, if we were interested in investigating the relationship between gender and attitudes towards music piracy amongst adolescents , the independent variable would be gender and the dependent variable attitudes towards music piracy . This example also highlights the need to identify the group(s) you are interested in. In this example, the group of interest are adolescents .

Once you identifying the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in, it is possible to start thinking about the way that the three types of quantitative research question can be structured . This is discussed next.

STEP THREE Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved

The structure of the three types of quantitative research question differs, reflecting the goals of the question, the types of variables, and the number of variables and groups involved. By structure , we mean the components of a research question (i.e., the types of variables, groups of interest), the number of these different components (i.e., how many variables and groups are being investigated), and the order that these should be presented (e.g., independent variables before dependent variables). The appropriate structure for each of these quantitative research questions is set out below:

Structure of descriptive research questions

• Structure of comparative research questions
• Structure of relationship-based research questions

There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group(s) you are interested in; (4) decide whether dependent variable or group(s) should be included first, last or in two parts; (5) include any words that provide greater context to your question; and (6) write out the descriptive research question. Each of these steps is discussed in turn:

Choose your starting phrase

Identify and name the dependent variable

Identify the group(s) you are interested in

Decide whether the dependent variable or group(s) should be included first, last or in two parts

Include any words that provide greater context to your question

Write out the descriptive research question

FIRST Choose your starting phrase

You can start descriptive research questions with any of the following phrases:

How many? How often? How frequently? How much? What percentage? What proportion? To what extent? What is? What are?

Some of these starting phrases are highlighted in blue text in the examples below:

How many calories do American men and women consume per day?

How often do British university students use Facebook each week?

What are the most important factors that influence the career choices of Australian university students?

What proportion of British male and female university students use the top 5 social networks?

What percentage of American men and women exceed their daily calorific allowance?

SECOND Identify and name the dependent variable

All descriptive research questions have a dependent variable. You need to identify what this is. However, how the dependent variable is written out in a research question and what you call it are often two different things. In the examples below, we have illustrated the name of the dependent variable and highlighted how it would be written out in the blue text .

The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.

THIRD Identify the group(s) you are interested in

All descriptive research questions have at least one group , but can have multiple groups . You need to identify this group(s). In the examples below, we have identified the group(s) in the green text .

What are the most important factors that influence the career choices of Australian university students ?

The examples illustrate the difference between the use of a single group (e.g., British university students ) and multiple groups (e.g., American men and women ).

FOURTH Decide whether the dependent variable or group(s) should be included first, last or in two parts

Sometimes it makes more sense for the dependent variable to appear before the group(s) you are interested in, but sometimes it is the opposite way around. The following examples illustrate this, with the group(s) in green text and the dependent variable in blue text :

Group 1st; dependent variable 2nd:

How often do British university students use Facebook each week ?

Dependent variable 1st; group 2nd:

Sometimes, the dependent variable needs to be broken into two parts around the group(s) you are interested in so that the research question flows. Again, the group(s) are in green text and the dependent variable is in blue text :

How many calories do American men and women consume per day ?

Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts. For example:

How many calories are consumed per day by American men and women ?

When deciding whether the dependent variable or group(s) should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow : Does the question flow? Is it easy to read?

FIFTH Include any words that provide greater context to your question

Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:

In the first example, the dependent variable is daily calorific intake (i.e., calories consumed per day). Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day. In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often (i.e., how frequently; e.g., 16 times per week) British university students use Facebook.

However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable. Take the following examples in red text :

In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable (i.e., the percentage of American men and women exceeding the recommend daily calorific allowance). In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.

Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question.

SIXTH Write out the descriptive research question

Once you have these details ? (1) the starting phrase, (2) the name of the dependent variable, (3) the name of the group(s) you are interested in, and (4) any potential joining words ? you can write out the descriptive research question in full. The example descriptive research questions discussed above are written out in full below:

In the section that follows, the structure of comparative research questions is discussed.

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Writing Research Papers

• Research Paper Structure

Whether you are writing a B.S. Degree Research Paper or completing a research report for a Psychology course, it is highly likely that you will need to organize your research paper in accordance with American Psychological Association (APA) guidelines.  Here we discuss the structure of research papers according to APA style.

Major Sections of a Research Paper in APA Style

A complete research paper in APA style that is reporting on experimental research will typically contain a Title page, Abstract, Introduction, Methods, Results, Discussion, and References sections. 1  Many will also contain Figures and Tables and some will have an Appendix or Appendices.  These sections are detailed as follows (for a more in-depth guide, please refer to " How to Write a Research Paper in APA Style ”, a comprehensive guide developed by Prof. Emma Geller). 2

What is this paper called and who wrote it? – the first page of the paper; this includes the name of the paper, a “running head”, authors, and institutional affiliation of the authors.  The institutional affiliation is usually listed in an Author Note that is placed towards the bottom of the title page.  In some cases, the Author Note also contains an acknowledgment of any funding support and of any individuals that assisted with the research project.

One-paragraph summary of the entire study – typically no more than 250 words in length (and in many cases it is well shorter than that), the Abstract provides an overview of the study.

Introduction

What is the topic and why is it worth studying? – the first major section of text in the paper, the Introduction commonly describes the topic under investigation, summarizes or discusses relevant prior research (for related details, please see the Writing Literature Reviews section of this website), identifies unresolved issues that the current research will address, and provides an overview of the research that is to be described in greater detail in the sections to follow.

What did you do? – a section which details how the research was performed.  It typically features a description of the participants/subjects that were involved, the study design, the materials that were used, and the study procedure.  If there were multiple experiments, then each experiment may require a separate Methods section.  A rule of thumb is that the Methods section should be sufficiently detailed for another researcher to duplicate your research.

What did you find? – a section which describes the data that was collected and the results of any statistical tests that were performed.  It may also be prefaced by a description of the analysis procedure that was used. If there were multiple experiments, then each experiment may require a separate Results section.

What is the significance of your results? – the final major section of text in the paper.  The Discussion commonly features a summary of the results that were obtained in the study, describes how those results address the topic under investigation and/or the issues that the research was designed to address, and may expand upon the implications of those findings.  Limitations and directions for future research are also commonly addressed.

List of articles and any books cited – an alphabetized list of the sources that are cited in the paper (by last name of the first author of each source).  Each reference should follow specific APA guidelines regarding author names, dates, article titles, journal titles, journal volume numbers, page numbers, book publishers, publisher locations, websites, and so on (for more information, please see the Citing References in APA Style page of this website).

Tables and Figures

Graphs and data (optional in some cases) – depending on the type of research being performed, there may be Tables and/or Figures (however, in some cases, there may be neither).  In APA style, each Table and each Figure is placed on a separate page and all Tables and Figures are included after the References.   Tables are included first, followed by Figures.   However, for some journals and undergraduate research papers (such as the B.S. Research Paper or Honors Thesis), Tables and Figures may be embedded in the text (depending on the instructor’s or editor’s policies; for more details, see "Deviations from APA Style" below).

Supplementary information (optional) – in some cases, additional information that is not critical to understanding the research paper, such as a list of experiment stimuli, details of a secondary analysis, or programming code, is provided.  This is often placed in an Appendix.

Variations of Research Papers in APA Style

Although the major sections described above are common to most research papers written in APA style, there are variations on that pattern.  These variations include: 

• Literature reviews – when a paper is reviewing prior published research and not presenting new empirical research itself (such as in a review article, and particularly a qualitative review), then the authors may forgo any Methods and Results sections. Instead, there is a different structure such as an Introduction section followed by sections for each of the different aspects of the body of research being reviewed, and then perhaps a Discussion section. 
• Multi-experiment papers – when there are multiple experiments, it is common to follow the Introduction with an Experiment 1 section, itself containing Methods, Results, and Discussion subsections. Then there is an Experiment 2 section with a similar structure, an Experiment 3 section with a similar structure, and so on until all experiments are covered.  Towards the end of the paper there is a General Discussion section followed by References.  Additionally, in multi-experiment papers, it is common for the Results and Discussion subsections for individual experiments to be combined into single “Results and Discussion” sections.

Departures from APA Style

In some cases, official APA style might not be followed (however, be sure to check with your editor, instructor, or other sources before deviating from standards of the Publication Manual of the American Psychological Association).  Such deviations may include:

• Placement of Tables and Figures  – in some cases, to make reading through the paper easier, Tables and/or Figures are embedded in the text (for example, having a bar graph placed in the relevant Results section). The embedding of Tables and/or Figures in the text is one of the most common deviations from APA style (and is commonly allowed in B.S. Degree Research Papers and Honors Theses; however you should check with your instructor, supervisor, or editor first). 
• Incomplete research – sometimes a B.S. Degree Research Paper in this department is written about research that is currently being planned or is in progress. In those circumstances, sometimes only an Introduction and Methods section, followed by References, is included (that is, in cases where the research itself has not formally begun).  In other cases, preliminary results are presented and noted as such in the Results section (such as in cases where the study is underway but not complete), and the Discussion section includes caveats about the in-progress nature of the research.  Again, you should check with your instructor, supervisor, or editor first.
• Class assignments – in some classes in this department, an assignment must be written in APA style but is not exactly a traditional research paper (for instance, a student asked to write about an article that they read, and to write that report in APA style). In that case, the structure of the paper might approximate the typical sections of a research paper in APA style, but not entirely.  You should check with your instructor for further guidelines.

Workshops and Downloadable Resources

• For in-person discussion of the process of writing research papers, please consider attending this department’s “Writing Research Papers” workshop (for dates and times, please check the undergraduate workshops calendar).

Downloadable Resources

• How to Write APA Style Research Papers (a comprehensive guide) [ PDF ]
• Tips for Writing APA Style Research Papers (a brief summary) [ PDF ]
• Example APA Style Research Paper (for B.S. Degree – empirical research) [ PDF ]
• Example APA Style Research Paper (for B.S. Degree – literature review) [ PDF ]

Further Resources

How-To Videos     

• Writing Research Paper Videos

APA Journal Article Reporting Guidelines

• Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M. (2018). Journal article reporting standards for quantitative research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 3.
• Levitt, H. M., Bamberg, M., Creswell, J. W., Frost, D. M., Josselson, R., & Suárez-Orozco, C. (2018). Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: The APA Publications and Communications Board task force report . American Psychologist , 73 (1), 26.  

External Resources

• Formatting APA Style Papers in Microsoft Word
• How to Write an APA Style Research Paper from Hamilton University
• WikiHow Guide to Writing APA Research Papers
• Sample APA Formatted Paper with Comments
• Sample APA Formatted Paper
• Tips for Writing a Paper in APA Style

1 VandenBos, G. R. (Ed). (2010). Publication manual of the American Psychological Association (6th ed.) (pp. 41-60).  Washington, DC: American Psychological Association.

2 geller, e. (2018).  how to write an apa-style research report . [instructional materials]. , prepared by s. c. pan for ucsd psychology.

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Home Market Research

Quantitative Research: What It Is, Practices & Methods

Quantitative research involves analyzing and gathering numerical data to uncover trends, calculate averages, evaluate relationships, and derive overarching insights. It’s used in various fields, including the natural and social sciences. Quantitative data analysis employs statistical techniques for processing and interpreting numeric data.

Research designs in the quantitative realm outline how data will be collected and analyzed with methods like experiments and surveys. Qualitative methods complement quantitative research by focusing on non-numerical data, adding depth to understanding. Data collection methods can be qualitative or quantitative, depending on research goals. Researchers often use a combination of both approaches to gain a comprehensive understanding of phenomena.

What is Quantitative Research?

Quantitative research is a systematic investigation of phenomena by gathering quantifiable data and performing statistical, mathematical, or computational techniques. Quantitative research collects statistically significant information from existing and potential customers using sampling methods and sending out online surveys , online polls , and questionnaires , for example.

One of the main characteristics of this type of research is that the results can be depicted in numerical form. After carefully collecting structured observations and understanding these numbers, it’s possible to predict the future of a product or service, establish causal relationships or Causal Research , and make changes accordingly. Quantitative research primarily centers on the analysis of numerical data and utilizes inferential statistics to derive conclusions that can be extrapolated to the broader population.

An example of a quantitative research study is the survey conducted to understand how long a doctor takes to tend to a patient when the patient walks into the hospital. A patient satisfaction survey can be administered to ask questions like how long a doctor takes to see a patient, how often a patient walks into a hospital, and other such questions, which are dependent variables in the research. This kind of research method is often employed in the social sciences, and it involves using mathematical frameworks and theories to effectively present data, ensuring that the results are logical, statistically sound, and unbiased.

Data collection in quantitative research uses a structured method and is typically conducted on larger samples representing the entire population. Researchers use quantitative methods to collect numerical data, which is then subjected to statistical analysis to determine statistically significant findings. This approach is valuable in both experimental research and social research, as it helps in making informed decisions and drawing reliable conclusions based on quantitative data.

Quantitative Research Characteristics

Quantitative research has several unique characteristics that make it well-suited for specific projects. Let’s explore the most crucial of these characteristics so that you can consider them when planning your next research project:

• Structured tools: Quantitative research relies on structured tools such as surveys, polls, or questionnaires to gather quantitative data . Using such structured methods helps collect in-depth and actionable numerical data from the survey respondents, making it easier to perform data analysis.
• Sample size: Quantitative research is conducted on a significant sample size  representing the target market . Appropriate Survey Sampling methods, a fundamental aspect of quantitative research methods, must be employed when deriving the sample to fortify the research objective and ensure the reliability of the results.
• Close-ended questions: Closed-ended questions , specifically designed to align with the research objectives, are a cornerstone of quantitative research. These questions facilitate the collection of quantitative data and are extensively used in data collection processes.
• Prior studies: Before collecting feedback from respondents, researchers often delve into previous studies related to the research topic. This preliminary research helps frame the study effectively and ensures the data collection process is well-informed.
• Quantitative data: Typically, quantitative data is represented using tables, charts, graphs, or other numerical forms. This visual representation aids in understanding the collected data and is essential for rigorous data analysis, a key component of quantitative research methods.
• Generalization of results: One of the strengths of quantitative research is its ability to generalize results to the entire population. It means that the findings derived from a sample can be extrapolated to make informed decisions and take appropriate actions for improvement based on numerical data analysis.

Quantitative Research Methods

Quantitative research methods are systematic approaches used to gather and analyze numerical data to understand and draw conclusions about a phenomenon or population. Here are the quantitative research methods:

• Primary quantitative research methods
• Secondary quantitative research methods

Primary Quantitative Research Methods

Primary quantitative research is the most widely used method of conducting market research. The distinct feature of primary research is that the researcher focuses on collecting data directly rather than depending on data collected from previously done research. Primary quantitative research design can be broken down into three further distinctive tracks and the process flow. They are:

A. Techniques and Types of Studies

There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are:

01. Survey Research

Survey Research is fundamental for all quantitative outcome research methodologies and studies. Surveys are used to ask questions to a sample of respondents, using various types such as online polls, online surveys, paper questionnaires, web-intercept surveys , etc. Every small and big organization intends to understand what their customers think about their products and services, how well new features are faring in the market, and other such details.

By conducting survey research, an organization can ask multiple survey questions , collect data from a pool of customers, and analyze this collected data to produce numerical results. It is the first step towards collecting data for any research. You can use single ease questions . A single-ease question is a straightforward query that elicits a concise and uncomplicated response.

This type of research can be conducted with a specific target audience group and also can be conducted across multiple groups along with comparative analysis . A prerequisite for this type of research is that the sample of respondents must have randomly selected members. This way, a researcher can easily maintain the accuracy of the obtained results as a huge variety of respondents will be addressed using random selection. 

Traditionally, survey research was conducted face-to-face or via phone calls. Still, with the progress made by online mediums such as email or social media, survey research has also spread to online mediums.There are two types of surveys , either of which can be chosen based on the time in hand and the kind of data required:

Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time. Researchers can evaluate various variables at a particular time. Data gathered using this type of survey is from people who depict similarity in all variables except the variables which are considered for research . Throughout the survey, this one variable will stay constant.

• Cross-sectional surveys are popular with retail, SMEs, and healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem.
• Multiple samples can be analyzed and compared using a cross-sectional survey research method.
• Multiple variables can be evaluated using this type of survey research.
• The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

Longitudinal surveys: Longitudinal surveys are also observational surveys , but unlike cross-sectional surveys, longitudinal surveys are conducted across various time durations to observe a change in respondent behavior and thought processes. This time can be days, months, years, or even decades. For instance, a researcher planning to analyze the change in buying habits of teenagers over 5 years will conduct longitudinal surveys.

• In cross-sectional surveys, the same variables were evaluated at a given time, and in longitudinal surveys, different variables can be analyzed at different intervals.
• Longitudinal surveys are extensively used in the field of medicine and applied sciences. Apart from these two fields, they are also used to observe a change in the market trend analysis , analyze customer satisfaction, or gain feedback on products/services.
• In situations where the sequence of events is highly essential, longitudinal surveys are used.
• Researchers say that when research subjects need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

02. Correlational Research

A comparison between two entities is invariable. Correlation research is conducted to establish a relationship between two closely-knit entities and how one impacts the other, and what changes are eventually observed. This research method is carried out to give value to naturally occurring relationships, and a minimum of two different groups are required to conduct this quantitative research method successfully. Without assuming various aspects, a relationship between two groups or entities must be established.

Researchers use this quantitative research design to correlate two or more variables using mathematical analysis methods. Patterns, relationships, and trends between variables are concluded as they exist in their original setup. The impact of one of these variables on the other is observed, along with how it changes the relationship between the two variables. Researchers tend to manipulate one of the variables to attain the desired results.

Ideally, it is advised not to make conclusions merely based on correlational research. This is because it is not mandatory that if two variables are in sync that they are interrelated.

Example of Correlational Research Questions :

• The relationship between stress and depression.
• The equation between fame and money.
• The relation between activities in a third-grade class and its students.

03. Causal-comparative Research

This research method mainly depends on the factor of comparison. Also called quasi-experimental research , this quantitative research method is used by researchers to conclude the cause-effect equation between two or more variables, where one variable is dependent on the other independent variable. The independent variable is established but not manipulated, and its impact on the dependent variable is observed. These variables or groups must be formed as they exist in the natural setup. As the dependent and independent variables will always exist in a group, it is advised that the conclusions are carefully established by keeping all the factors in mind.

Causal-comparative research is not restricted to the statistical analysis of two variables but extends to analyzing how various variables or groups change under the influence of the same changes. This research is conducted irrespective of the type of relationship that exists between two or more variables. Statistical analysis plan is used to present the outcome using this quantitative research method.

Example of Causal-Comparative Research Questions:

• The impact of drugs on a teenager. The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa.

04. Experimental Research

Also known as true experimentation, this research method relies on a theory. As the name suggests, experimental research is usually based on one or more theories. This theory has yet to be proven before and is merely a supposition. In experimental research, an analysis is done around proving or disproving the statement. This research method is used in natural sciences. Traditional research methods are more effective than modern techniques.

There can be multiple theories in experimental research. A theory is a statement that can be verified or refuted.

After establishing the statement, efforts are made to understand whether it is valid or invalid. This quantitative research method is mainly used in natural or social sciences as various statements must be proved right or wrong.

• Traditional research methods are more effective than modern techniques.
• Systematic teaching schedules help children who struggle to cope with the course.
• It is a boon to have responsible nursing staff for ailing parents.

B. Data Collection Methodologies

The second major step in primary quantitative research is data collection. Data collection can be divided into sampling methods and data collection using surveys and polls.

01. Data Collection Methodologies: Sampling Methods

There are two main sampling methods for quantitative research: Probability and Non-probability sampling .

Probability sampling: A theory of probability is used to filter individuals from a population and create samples in probability sampling . Participants of a sample are chosen by random selection processes. Each target audience member has an equal opportunity to be selected in the sample.

There are four main types of probability sampling:

• Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.
• Stratified random sampling: In the stratified random sampling method , a large population is divided into groups (strata), and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another.
• Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic segmentation and demographic segmentation parameters.
• Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.

Non-probability sampling: Non-probability sampling is where the researcher’s knowledge and experience are used to create samples. Because of the researcher’s involvement, not all the target population members have an equal probability of being selected to be a part of a sample.

There are five non-probability sampling models:

• Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved.
• Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.
• Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Members of various strata can then be chosen to be a part of the sample as per the researcher’s understanding.
• Snowball sampling: Snowball sampling is conducted with target audiences who are difficult to contact and get information. It is popular in cases where the target audience for analysis research is rare to put together.
• Judgmental sampling: Judgmental sampling is a non-probability sampling method where samples are created only based on the researcher’s experience and research skill .

02. Data collection methodologies: Using surveys & polls

Once the sample is determined, then either surveys or polls can be distributed to collect the data for quantitative research.

Using surveys for primary quantitative research

A survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest. The ease of survey distribution and the wide number of people it can reach depending on the research time and objective makes it one of the most important aspects of conducting quantitative research.

Fundamental levels of measurement – nominal, ordinal, interval, and ratio scales

Four measurement scales are fundamental to creating a multiple-choice question in a survey. They are nominal, ordinal, interval, and ratio measurement scales without the fundamentals of which no multiple-choice questions can be created. Hence, it is crucial to understand these measurement levels to develop a robust survey.

Use of different question types

To conduct quantitative research, close-ended questions must be used in a survey. They can be a mix of multiple question types, including multiple-choice questions like semantic differential scale questions , rating scale questions , etc.

Survey Distribution and Survey Data Collection

In the above, we have seen the process of building a survey along with the research design to conduct primary quantitative research. Survey distribution to collect data is the other important aspect of the survey process. There are different ways of survey distribution. Some of the most commonly used methods are:

• Email: Sending a survey via email is the most widely used and effective survey distribution method. This method’s response rate is high because the respondents know your brand. You can use the QuestionPro email management feature to send out and collect survey responses.
• Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample. Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher.
• Embed survey on a website: Embedding a survey on a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.
• Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand.
• QR code: QuestionPro QR codes store the URL for the survey. You can print/publish this code in magazines, signs, business cards, or on just about any object/medium.
• SMS survey: The SMS survey is a quick and time-effective way to collect a high number of responses.
• Offline Survey App: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline.

Survey example

An example of a survey is a short customer satisfaction (CSAT) survey that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.

Using polls for primary quantitative research

Polls are a method to collect feedback using close-ended questions from a sample. The most commonly used types of polls are election polls and exit polls . Both of these are used to collect data from a large sample size but using basic question types like multiple-choice questions.

C. Data Analysis Techniques

The third aspect of primary quantitative research design is data analysis . After collecting raw data, there must be an analysis of this data to derive statistical inferences from this research. It is important to relate the results to the research objective and establish the statistical relevance of the results.

Remember to consider aspects of research that were not considered for the data collection process and report the difference between what was planned vs. what was actually executed.

It is then required to select precise Statistical Analysis Methods , such as SWOT, Conjoint, Cross-tabulation, etc., to analyze the quantitative data.

• SWOT analysis: SWOT Analysis stands for the acronym of Strengths, Weaknesses, Opportunities, and Threat analysis. Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement.
• Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions. Trade-offs are involved in an individual’s daily activities, and these reflect their ability to decide from a complex list of product/service options.
• Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study.
• TURF Analysis: TURF Analysis , an acronym for Totally Unduplicated Reach and Frequency Analysis, is executed in situations where the reach of a favorable communication source is to be analyzed along with the frequency of this communication. It is used for understanding the potential of a target market.

Inferential statistics methods such as confidence interval, the margin of error, etc., can then be used to provide results.

Secondary Quantitative Research Methods

Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data. Existing data is summarized and collated to increase the overall effectiveness of the research.

This research method involves collecting quantitative data from existing data sources like the internet, government resources, libraries, research reports, etc. Secondary quantitative research helps to validate the data collected from primary quantitative research and aid in strengthening or proving, or disproving previously collected data.

The following are five popularly used secondary quantitative research methods:

• Data available on the internet: With the high penetration of the internet and mobile devices, it has become increasingly easy to conduct quantitative research using the internet. Information about most research topics is available online, and this aids in boosting the validity of primary quantitative data.
• Government and non-government sources: Secondary quantitative research can also be conducted with the help of government and non-government sources that deal with market research reports. This data is highly reliable and in-depth and hence, can be used to increase the validity of quantitative research design.
• Public libraries: Now a sparingly used method of conducting quantitative research, it is still a reliable source of information, though. Public libraries have copies of important research that was conducted earlier. They are a storehouse of valuable information and documents from which information can be extracted.
• Educational institutions: Educational institutions conduct in-depth research on multiple topics, and hence, the reports that they publish are an important source of validation in quantitative research.
• Commercial information sources: Local newspapers, journals, magazines, radio, and TV stations are great sources to obtain data for secondary quantitative research. These commercial information sources have in-depth, first-hand information on market research, demographic segmentation, and similar subjects.

Quantitative Research Examples

Some examples of quantitative research are:

• A customer satisfaction template can be used if any organization would like to conduct a customer satisfaction (CSAT) survey . Through this kind of survey, an organization can collect quantitative data and metrics on the goodwill of the brand or organization in the customer’s mind based on multiple parameters such as product quality, pricing, customer experience, etc. This data can be collected by asking a net promoter score (NPS) question , matrix table questions, etc. that provide data in the form of numbers that can be analyzed and worked upon.
• Another example of quantitative research is an organization that conducts an event, collecting feedback from attendees about the value they see from the event. By using an event survey , the organization can collect actionable feedback about the satisfaction levels of customers during various phases of the event such as the sales, pre and post-event, the likelihood of recommending the organization to their friends and colleagues, hotel preferences for the future events and other such questions.

What are the Advantages of Quantitative Research?

There are many advantages to quantitative research. Some of the major advantages of why researchers use this method in market research are:

Collect Reliable and Accurate Data:

Quantitative research is a powerful method for collecting reliable and accurate quantitative data. Since data is collected, analyzed, and presented in numbers, the results obtained are incredibly reliable and objective. Numbers do not lie and offer an honest and precise picture of the conducted research without discrepancies. In situations where a researcher aims to eliminate bias and predict potential conflicts, quantitative research is the method of choice.

Quick Data Collection:

Quantitative research involves studying a group of people representing a larger population. Researchers use a survey or another quantitative research method to efficiently gather information from these participants, making the process of analyzing the data and identifying patterns faster and more manageable through the use of statistical analysis. This advantage makes quantitative research an attractive option for projects with time constraints.

Wider Scope of Data Analysis:

Quantitative research, thanks to its utilization of statistical methods, offers an extensive range of data collection and analysis. Researchers can delve into a broader spectrum of variables and relationships within the data, enabling a more thorough comprehension of the subject under investigation. This expanded scope is precious when dealing with complex research questions that require in-depth numerical analysis.

Eliminate Bias:

One of the significant advantages of quantitative research is its ability to eliminate bias. This research method leaves no room for personal comments or the biasing of results, as the findings are presented in numerical form. This objectivity makes the results fair and reliable in most cases, reducing the potential for researcher bias or subjectivity.

In summary, quantitative research involves collecting, analyzing, and presenting quantitative data using statistical analysis. It offers numerous advantages, including the collection of reliable and accurate data, quick data collection, a broader scope of data analysis, and the elimination of bias, making it a valuable approach in the field of research. When considering the benefits of quantitative research, it’s essential to recognize its strengths in contrast to qualitative methods and its role in collecting and analyzing numerical data for a more comprehensive understanding of research topics.

Best Practices to Conduct Quantitative Research

Here are some best practices for conducting quantitative research:

• Differentiate between quantitative and qualitative: Understand the difference between the two methodologies and apply the one that suits your needs best.
• Choose a suitable sample size: Ensure that you have a sample representative of your population and large enough to be statistically weighty.
• Keep your research goals clear and concise: Know your research goals before you begin data collection to ensure you collect the right amount and the right quantity of data.
• Keep the questions simple: Remember that you will be reaching out to a demographically wide audience. Pose simple questions for your respondents to understand easily.

Quantitative Research vs Qualitative Research

Quantitative research and qualitative research are two distinct approaches to conducting research, each with its own set of methods and objectives. Here’s a comparison of the two:

Quantitative Research

• Objective: The primary goal of quantitative research is to quantify and measure phenomena by collecting numerical data. It aims to test hypotheses, establish patterns, and generalize findings to a larger population.
• Data Collection: Quantitative research employs systematic and standardized approaches for data collection, including techniques like surveys, experiments, and observations that involve predefined variables. It is often collected from a large and representative sample.
• Data Analysis: Data is analyzed using statistical techniques, such as descriptive statistics, inferential statistics, and mathematical modeling. Researchers use statistical tests to draw conclusions and make generalizations based on numerical data.
• Sample Size: Quantitative research often involves larger sample sizes to ensure statistical significance and generalizability.
• Results: The results are typically presented in tables, charts, and statistical summaries, making them highly structured and objective.
• Generalizability: Researchers intentionally structure quantitative research to generate outcomes that can be helpful to a larger population, and they frequently seek to establish causative connections.
• Emphasis on Objectivity: Researchers aim to minimize bias and subjectivity, focusing on replicable and objective findings.

Qualitative Research

• Objective: Qualitative research seeks to gain a deeper understanding of the underlying motivations, behaviors, and experiences of individuals or groups. It explores the context and meaning of phenomena.
• Data Collection: Qualitative research employs adaptable and open-ended techniques for data collection, including methods like interviews, focus groups, observations, and content analysis. It allows participants to express their perspectives in their own words.
• Data Analysis: Data is analyzed through thematic analysis, content analysis, or grounded theory. Researchers focus on identifying patterns, themes, and insights in the data.
• Sample Size: Qualitative research typically involves smaller sample sizes due to the in-depth nature of data collection and analysis.
• Results: Findings are presented in narrative form, often in the participants’ own words. Results are subjective, context-dependent, and provide rich, detailed descriptions.
• Generalizability: Qualitative research does not aim for broad generalizability but focuses on in-depth exploration within a specific context. It provides a detailed understanding of a particular group or situation.
• Emphasis on Subjectivity: Researchers acknowledge the role of subjectivity and the researcher’s influence on the Research Process . Participant perspectives and experiences are central to the findings.

Researchers choose between quantitative and qualitative research methods based on their research objectives and the nature of the research question. Each approach has its advantages and drawbacks, and the decision between them hinges on the particular research objectives and the data needed to address research inquiries effectively.

Quantitative research is a structured way of collecting and analyzing data from various sources. Its purpose is to quantify the problem and understand its extent, seeking results that someone can project to a larger population.

Companies that use quantitative rather than qualitative research typically aim to measure magnitudes and seek objectively interpreted statistical results. So if you want to obtain quantitative data that helps you define the structured cause-and-effect relationship between the research problem and the factors, you should opt for this type of research.

At QuestionPro , we have various Best Data Collection Tools and features to conduct investigations of this type. You can create questionnaires and distribute them through our various methods. We also have sample services or various questions to guarantee the success of your study and the quality of the collected data.

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Quantitative research is a systematic and structured approach to studying phenomena that involves the collection of measurable data and the application of statistical, mathematical, or computational techniques for analysis.

Quantitative research is characterized by structured tools like surveys, substantial sample sizes, closed-ended questions, reliance on prior studies, data presented numerically, and the ability to generalize findings to the broader population.

The two main methods of quantitative research are Primary quantitative research methods, involving data collection directly from sources, and Secondary quantitative research methods, which utilize existing data for analysis.

1.Surveying to measure employee engagement with numerical rating scales. 2.Analyzing sales data to identify trends in product demand and market share. 4.Examining test scores to assess the impact of a new teaching method on student performance. 4.Using website analytics to track user behavior and conversion rates for an online store.

1.Differentiate between quantitative and qualitative approaches. 2.Choose a representative sample size. 3.Define clear research goals before data collection. 4.Use simple and easily understandable survey questions.

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