rules of research papers

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13.1 Formatting a Research Paper

Learning objectives.

• Identify the major components of a research paper written using American Psychological Association (APA) style.
• Apply general APA style and formatting conventions in a research paper.

In this chapter, you will learn how to use APA style , the documentation and formatting style followed by the American Psychological Association, as well as MLA style , from the Modern Language Association. There are a few major formatting styles used in academic texts, including AMA, Chicago, and Turabian:

• AMA (American Medical Association) for medicine, health, and biological sciences
• APA (American Psychological Association) for education, psychology, and the social sciences
• Chicago—a common style used in everyday publications like magazines, newspapers, and books
• MLA (Modern Language Association) for English, literature, arts, and humanities
• Turabian—another common style designed for its universal application across all subjects and disciplines

While all the formatting and citation styles have their own use and applications, in this chapter we focus our attention on the two styles you are most likely to use in your academic studies: APA and MLA.

If you find that the rules of proper source documentation are difficult to keep straight, you are not alone. Writing a good research paper is, in and of itself, a major intellectual challenge. Having to follow detailed citation and formatting guidelines as well may seem like just one more task to add to an already-too-long list of requirements.

Following these guidelines, however, serves several important purposes. First, it signals to your readers that your paper should be taken seriously as a student’s contribution to a given academic or professional field; it is the literary equivalent of wearing a tailored suit to a job interview. Second, it shows that you respect other people’s work enough to give them proper credit for it. Finally, it helps your reader find additional materials if he or she wishes to learn more about your topic.

Furthermore, producing a letter-perfect APA-style paper need not be burdensome. Yes, it requires careful attention to detail. However, you can simplify the process if you keep these broad guidelines in mind:

• Work ahead whenever you can. Chapter 11 “Writing from Research: What Will I Learn?” includes tips for keeping track of your sources early in the research process, which will save time later on.
• Get it right the first time. Apply APA guidelines as you write, so you will not have much to correct during the editing stage. Again, putting in a little extra time early on can save time later.
• Use the resources available to you. In addition to the guidelines provided in this chapter, you may wish to consult the APA website at http://www.apa.org or the Purdue University Online Writing lab at http://owl.english.purdue.edu , which regularly updates its online style guidelines.

General Formatting Guidelines

This chapter provides detailed guidelines for using the citation and formatting conventions developed by the American Psychological Association, or APA. Writers in disciplines as diverse as astrophysics, biology, psychology, and education follow APA style. The major components of a paper written in APA style are listed in the following box.

These are the major components of an APA-style paper:

Body, which includes the following:

• Headings and, if necessary, subheadings to organize the content
• In-text citations of research sources
• References page

All these components must be saved in one document, not as separate documents.

The title page of your paper includes the following information:

• Title of the paper
• Author’s name
• Name of the institution with which the author is affiliated
• Header at the top of the page with the paper title (in capital letters) and the page number (If the title is lengthy, you may use a shortened form of it in the header.)

List the first three elements in the order given in the previous list, centered about one third of the way down from the top of the page. Use the headers and footers tool of your word-processing program to add the header, with the title text at the left and the page number in the upper-right corner. Your title page should look like the following example.

The next page of your paper provides an abstract , or brief summary of your findings. An abstract does not need to be provided in every paper, but an abstract should be used in papers that include a hypothesis. A good abstract is concise—about one hundred fifty to two hundred fifty words—and is written in an objective, impersonal style. Your writing voice will not be as apparent here as in the body of your paper. When writing the abstract, take a just-the-facts approach, and summarize your research question and your findings in a few sentences.

In Chapter 12 “Writing a Research Paper” , you read a paper written by a student named Jorge, who researched the effectiveness of low-carbohydrate diets. Read Jorge’s abstract. Note how it sums up the major ideas in his paper without going into excessive detail.

Write an abstract summarizing your paper. Briefly introduce the topic, state your findings, and sum up what conclusions you can draw from your research. Use the word count feature of your word-processing program to make sure your abstract does not exceed one hundred fifty words.

Depending on your field of study, you may sometimes write research papers that present extensive primary research, such as your own experiment or survey. In your abstract, summarize your research question and your findings, and briefly indicate how your study relates to prior research in the field.

Margins, Pagination, and Headings

APA style requirements also address specific formatting concerns, such as margins, pagination, and heading styles, within the body of the paper. Review the following APA guidelines.

Use these general guidelines to format the paper:

• Set the top, bottom, and side margins of your paper at 1 inch.
• Use double-spaced text throughout your paper.
• Use a standard font, such as Times New Roman or Arial, in a legible size (10- to 12-point).
• Use continuous pagination throughout the paper, including the title page and the references section. Page numbers appear flush right within your header.
• Section headings and subsection headings within the body of your paper use different types of formatting depending on the level of information you are presenting. Additional details from Jorge’s paper are provided.

Begin formatting the final draft of your paper according to APA guidelines. You may work with an existing document or set up a new document if you choose. Include the following:

• Your title page
• The abstract you created in Note 13.8 “Exercise 1”
• Correct headers and page numbers for your title page and abstract

APA style uses section headings to organize information, making it easy for the reader to follow the writer’s train of thought and to know immediately what major topics are covered. Depending on the length and complexity of the paper, its major sections may also be divided into subsections, sub-subsections, and so on. These smaller sections, in turn, use different heading styles to indicate different levels of information. In essence, you are using headings to create a hierarchy of information.

The following heading styles used in APA formatting are listed in order of greatest to least importance:

• Section headings use centered, boldface type. Headings use title case, with important words in the heading capitalized.
• Subsection headings use left-aligned, boldface type. Headings use title case.
• The third level uses left-aligned, indented, boldface type. Headings use a capital letter only for the first word, and they end in a period.
• The fourth level follows the same style used for the previous level, but the headings are boldfaced and italicized.
• The fifth level follows the same style used for the previous level, but the headings are italicized and not boldfaced.

Visually, the hierarchy of information is organized as indicated in Table 13.1 “Section Headings” .

Table 13.1 Section Headings

A college research paper may not use all the heading levels shown in Table 13.1 “Section Headings” , but you are likely to encounter them in academic journal articles that use APA style. For a brief paper, you may find that level 1 headings suffice. Longer or more complex papers may need level 2 headings or other lower-level headings to organize information clearly. Use your outline to craft your major section headings and determine whether any subtopics are substantial enough to require additional levels of headings.

Working with the document you developed in Note 13.11 “Exercise 2” , begin setting up the heading structure of the final draft of your research paper according to APA guidelines. Include your title and at least two to three major section headings, and follow the formatting guidelines provided above. If your major sections should be broken into subsections, add those headings as well. Use your outline to help you.

Because Jorge used only level 1 headings, his Exercise 3 would look like the following:

Citation Guidelines

In-text citations.

Throughout the body of your paper, include a citation whenever you quote or paraphrase material from your research sources. As you learned in Chapter 11 “Writing from Research: What Will I Learn?” , the purpose of citations is twofold: to give credit to others for their ideas and to allow your reader to follow up and learn more about the topic if desired. Your in-text citations provide basic information about your source; each source you cite will have a longer entry in the references section that provides more detailed information.

In-text citations must provide the name of the author or authors and the year the source was published. (When a given source does not list an individual author, you may provide the source title or the name of the organization that published the material instead.) When directly quoting a source, it is also required that you include the page number where the quote appears in your citation.

This information may be included within the sentence or in a parenthetical reference at the end of the sentence, as in these examples.

Epstein (2010) points out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Here, the writer names the source author when introducing the quote and provides the publication date in parentheses after the author’s name. The page number appears in parentheses after the closing quotation marks and before the period that ends the sentence.

Addiction researchers caution that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (Epstein, 2010, p. 137).

Here, the writer provides a parenthetical citation at the end of the sentence that includes the author’s name, the year of publication, and the page number separated by commas. Again, the parenthetical citation is placed after the closing quotation marks and before the period at the end of the sentence.

As noted in the book Junk Food, Junk Science (Epstein, 2010, p. 137), “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive.”

Here, the writer chose to mention the source title in the sentence (an optional piece of information to include) and followed the title with a parenthetical citation. Note that the parenthetical citation is placed before the comma that signals the end of the introductory phrase.

David Epstein’s book Junk Food, Junk Science (2010) pointed out that “junk food cannot be considered addictive in the same way that we think of psychoactive drugs as addictive” (p. 137).

Another variation is to introduce the author and the source title in your sentence and include the publication date and page number in parentheses within the sentence or at the end of the sentence. As long as you have included the essential information, you can choose the option that works best for that particular sentence and source.

Citing a book with a single author is usually a straightforward task. Of course, your research may require that you cite many other types of sources, such as books or articles with more than one author or sources with no individual author listed. You may also need to cite sources available in both print and online and nonprint sources, such as websites and personal interviews. Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.2 “Citing and Referencing Techniques” and Section 13.3 “Creating a References Section” provide extensive guidelines for citing a variety of source types.

Writing at Work

APA is just one of several different styles with its own guidelines for documentation, formatting, and language usage. Depending on your field of interest, you may be exposed to additional styles, such as the following:

• MLA style. Determined by the Modern Languages Association and used for papers in literature, languages, and other disciplines in the humanities.
• Chicago style. Outlined in the Chicago Manual of Style and sometimes used for papers in the humanities and the sciences; many professional organizations use this style for publications as well.
• Associated Press (AP) style. Used by professional journalists.

References List

The brief citations included in the body of your paper correspond to the more detailed citations provided at the end of the paper in the references section. In-text citations provide basic information—the author’s name, the publication date, and the page number if necessary—while the references section provides more extensive bibliographical information. Again, this information allows your reader to follow up on the sources you cited and do additional reading about the topic if desired.

The specific format of entries in the list of references varies slightly for different source types, but the entries generally include the following information:

• The name(s) of the author(s) or institution that wrote the source
• The year of publication and, where applicable, the exact date of publication
• The full title of the source
• For books, the city of publication
• For articles or essays, the name of the periodical or book in which the article or essay appears
• For magazine and journal articles, the volume number, issue number, and pages where the article appears
• For sources on the web, the URL where the source is located

The references page is double spaced and lists entries in alphabetical order by the author’s last name. If an entry continues for more than one line, the second line and each subsequent line are indented five spaces. Review the following example. ( Chapter 13 “APA and MLA Documentation and Formatting” , Section 13.3 “Creating a References Section” provides extensive guidelines for formatting reference entries for different types of sources.)

In APA style, book and article titles are formatted in sentence case, not title case. Sentence case means that only the first word is capitalized, along with any proper nouns.

Key Takeaways

• Following proper citation and formatting guidelines helps writers ensure that their work will be taken seriously, give proper credit to other authors for their work, and provide valuable information to readers.
• Working ahead and taking care to cite sources correctly the first time are ways writers can save time during the editing stage of writing a research paper.
• APA papers usually include an abstract that concisely summarizes the paper.
• APA papers use a specific headings structure to provide a clear hierarchy of information.
• In APA papers, in-text citations usually include the name(s) of the author(s) and the year of publication.
• In-text citations correspond to entries in the references section, which provide detailed bibliographical information about a source.

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Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

Table of Contents

Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

• Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
• Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
• Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
• Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
• Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
• Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
• Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
• Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
• Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

• Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
• Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
• Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

• How often do you use social media per day?
• Less than 30 minutes
• 30 minutes to 1 hour
• 1 to 2 hours
• 2 to 4 hours
• More than 4 hours
• Which social media platforms do you use?
• Others (Please specify)
• How often do you experience the following on social media?
• Social comparison (comparing yourself to others)
• Cyberbullying
• Fear of Missing Out (FOMO)
• Have you ever experienced any of the following mental health problems in the past month?
• Do you think social media use has a positive or negative impact on your mental health?
• Very positive
• Somewhat positive
• Somewhat negative
• Very negative
• In your opinion, which factors contribute to the negative impact of social media on mental health?
• Social comparison
• In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
• Education on healthy social media use
• Counseling for mental health problems caused by social media
• Social media detox programs
• Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

• Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
• Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
• Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
• Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
• Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

• For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
• For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
• To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
• To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

• To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
• To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
• To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
• To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

• Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
• Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
• Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
• Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
• Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
• Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

• Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
• Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
• Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
• Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
• Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
• Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

• Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
• Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
• Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
• Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
• Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
• Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to format a research paper

Last updated

7 February 2023

Reviewed by

Miroslav Damyanov

Writing a research paper can be daunting if you’re not experienced with the process. Getting the proper format is one of the most challenging aspects of the task. Reviewers will immediately dismiss a paper that doesn't comply with standard formatting, regardless of the valuable content it contains. 

In this article, we'll delve into the essential characteristics of a research paper, including the proper formatting.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• What is a research paper?

A research paper is a document that provides a thorough analysis of a topic , usually for an academic institution or professional organization. A research paper may be of any length, but they are typically 2,000–10,000 words. 

Unlike less formal papers, such as articles or essays, empirical evidence and data are key to research papers. In addition to students handing in papers, scientists, attorneys, medical researchers, and independent scholars may need to produce research papers.

People typically write research papers to prove a particular point or make an argument. This could support or disprove a theoretical point, legal case, scientific theory, or an existing piece of research on any topic. 

One of the distinguishing characteristics of research papers is that they contain citations to prior research. Citing sources using the correct format is essential for creating a legitimate research paper. 

• Top considerations for writing a research paper

To write a research paper, you must consider several factors. Fields such as the sciences, humanities, and technical professions have certain criteria for writing research papers. 

You’ll write a research paper using one of several types of formatting. These include APA, MLA, and CMOS styles, which we’ll cover in detail to guide you on citations and other formatting rules. 

Specific requirements of the assignment

If the paper is for a college, university, or any specific organization, they’ll give you certain requirements, such as the range of topics, length, and formatting requirements.

You should study the specifics of the assignment carefully, as these will override more general guidelines you may find elsewhere. If you're writing for a particular professor, they may ask for single or double spacing or a certain citation style. 

• Components of a research paper

Here are the basic steps to writing a quality research paper, assuming you've chosen your topic and considered the requirements of the paper. Depending on the specific conditions of the paper you're writing, you may need the following elements:

Thesis statement

The thesis statement provides a blueprint for the paper. It conveys the theme and purpose of the paper. It also informs you and readers what your paper will argue and the type of research it will contain. As you write the paper, you can refer to the thesis statement to help you decide whether or not to include certain items.

Most research papers require an abstract as well as a thesis. While the thesis is a short (usually a single sentence) summary of the work, an abstract contains more detail. Many papers use the IMRaD structure for the abstract, especially in scientific fields. This consists of four elements:

Introduction : Summarize the purpose of the paper

Methods : Describe the research methods (e.g., collecting data , interviews , field research)

Results: Summarize your conclusions.  

Discussion: Discuss the implications of your research. Mention any significant limitations to your approach and suggest areas for further research.

The thesis and abstract come at the beginning of a paper, but you should write them after completing the paper. This approach ensures a clear idea of your main topic and argument, which can evolve as you write the paper.

Table of contents

Like most nonfiction books, a research paper usually includes a table of contents. 

Tables, charts, and illustrations

If your paper contains multiple tables, charts, illustrations, or other graphics, you can create a list of these. 

Works cited or reference page

This page lists all the works you cited in your paper. For MLA and APA styles, you will use in-text citations in the body of the paper. For Chicago (CMOS) style, you'll use footnotes. 

Bibliography

While you use a reference page to note all cited papers, a bibliography lists all the works you consulted in your research, even if you don't specifically cite them. 

While references are essential, a bibliography is optional but usually advisable to demonstrate the breadth of your research.

Dedication and acknowledgments

You may include a dedication or acknowledgments at the beginning of the paper directly after the title page and before the abstract.

• Steps for writing a research paper

These are the most critical steps for researching, writing, and formatting a research paper:

Create an outline

The outline is not part of the published paper; it’s for your use. An outline makes it easier to structure the paper, ensuring you include all necessary points and research. 

Here you can list all topics and subtopics that will support your argument. When doing your research, you can refer to the outline to ensure you include everything. 

Gather research

Solid research is the hallmark of a research paper. In addition to accumulating research, you need to present it clearly. However, gathering research is one of the first tasks. If you compile each piece of research correctly, it will be easier to format the paper correctly. You want to avoid having to go back and look up information constantly.

Start by skimming potentially useful sources and putting them aside for later use. Reading each source thoroughly at this stage will be time-consuming and slow your progress. You can thoroughly review the sources to decide what to include and discard later. At this stage, note essential information such as names, dates, page numbers, and website links. Citing sources will be easier when you’ve written all the information down.

Be aware of the quality of your sources. A research paper should reference scholarly, academic, or scientific journals. It’s vital to understand the difference between primary and secondary sources. 

A primary source is an original, firsthand account of a topic. A secondary source is someone else covering the topic, as in a popular article or interview. While you may include secondary sources, your paper should also include primary research . Online research can be convenient, but you need to be extra careful when assessing the quality of your sources.

Write the first draft

Create a first draft where you put together all your research and address the topic described in your thesis and abstract. 

Edit and format the paper

Proofread, edit, and make any necessary adjustments and improvements to the first draft. List your citations as described below. Ensure your thesis and abstract describe your research accurately. 

• Formatting a research paper: MLA, APA, and CMOS styles

There are several popular formats for research papers: MLA (Modern Language Association) and APA (American Psychological Association). Certain academic papers use CMOS (Chicago Manual of Style). Other formats may apply to particular fields. 

For example, medical research may use AMA (American Medical Association) formatting and IEEE (Institute of Electrical and Electronics Engineers) for particular technical papers. The following are the guidelines and examples of the most popular formats:

The humanities typically use MLA format, including literature, history, and culture. Look over examples of papers created in MLA format . Here are the main rules to keep in mind:

Double-spaced lines.

Indent new paragraphs 1/2 inch.

Title case for headings, where all major words are capitalized, as in "How to Write a Research Paper." 

Use a popular font such as Times New Roman. This applies to all formatting styles.

Use one-inch margins on all sides. 

Number sections of the paper using Arabic numerals (1, 2, 3, etc.). 

Use a running head for each page on the upper right-hand corner, which consists of your last name and the page number.

Use an in-text citation within the text, using the author's last name followed by the page number: "Anything worth dying for is certainly worth living for" (Heller 155).  

On the citations page, list the full name, book or periodical, and other information. For MLA, you will not need footnotes, only in-text citations.

List citations in alphabetical order on a separate page at the end of the paper entitled “Works Cited.” 

Continuing with the above example from Heller, the listing would be: Heller, Joseph. Catch-22, Simon & Schuster, 1961.

For a periodical, the format is "Thompson, Hunter S. "The Kentucky Derby is Decadent and Depraved" Scanlon's, June 1970."

Use title case for source titles, as in "On the Origin of Species."

The sciences typically use APA format, including physical sciences such as physics and social sciences such as psychology. Simply Psychology provides examples of APA formatting . The following are the most important rules of the APA format.

Begin the paper with a title page, which is not required for MLA.

Use double-line spacing.

Use a running head for each page in the upper right-hand corner, which consists of the paper's title in capital letters followed by the page number.

The citations page at the end should be titled "References."

In-text citations should include the publication date: (Smith, 1999, p. 50). Note also that there's a "p" for "page," whereas in MLA, you write the page number without a "p."

As with MLA, use title case for headings, as in "Most Popular Treatments for Cognitive Disorders."

Use sentence case for titles of sources, as in "History of the decline and fall of the Roman empire." Note "Roman" starts with a capital because it's a proper noun.  

When citing in-text references, use the author's last name and the first and middle initials. 

Always use the Oxford comma. This comma goes before the words "or" and "and" in a list. For example, "At the store, I bought oranges, paper towels, and pasta."

CMOS formatting

Book publishers and many academic papers use CMOS formatting based on the Chicago Manual of Style. CMOS is also called Turabian, named after Kate L. Turabian, who wrote the first manual for this style. Here are examples of CMOS style formatting and citations.

Include an unnumbered title page.

Place page numbers on the upper right-hand corner of the page. Do not list your name or the paper's title as you would for MLA or APA styles.

Use title case for both headings and sources (same as MLA).

Unlike MLA and APA, the Chicago style uses footnotes for citations. Use a superscript for footnotes: "Smith argues against Jones' theory¹.” Footnotes may appear at the bottom of the page or the end of the document.  

CMOS supports both short notes and full notes. In most cases, you'll use the full note: "Michael Pollan, The Omnivore's Dilemma: A Natural History of Four Meals (New York: Penguin, 2006), 76." For further references to the same source, use a short note: " Pollan, Omnivore's Dilemma, 45." The requirements of some papers may specify using only short notes for all footnotes.

• General guidelines for writing and formatting research papers

Keep these guidelines in mind for all types of research papers:

Initial formatting

As you create your first draft, don't worry about formatting. If you try to format it perfectly as you write the paper, it will be difficult to progress and develop a flow of thought. With the first draft, you don't have to be concerned about ordering the sections. You can rearrange headings and sections later. 

Citation tools

Use automation tools for citations . Some useful tools make citations easier by automatically generating a citation list and bibliography. Many work with APA, MLA, and CMOS styles.

Check for plagiarism

Use a plagiarism detector to make sure your paper isn't unintentionally plagiarizing. There are many free and paid plagiarism checkers online, such as Grammarly. 

Proofread your work

Do several rounds of editing and proofreading. Editing is necessary for any type of writing, but you’ll need to revisit several distinct areas with a research paper:

Check for spelling and grammatical errors.

Read the paper to make sure it's well-argued and that you’ve organized it properly. 

Check that you’ve correctly formatted citations. It's easy to make errors, such as incorrect numbering of footnotes (e.g., Chicago style) or forgetting to include a source on your citations page.

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Writing a Research Paper

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The Research Paper

There will come a time in most students' careers when they are assigned a research paper. Such an assignment often creates a great deal of unneeded anxiety in the student, which may result in procrastination and a feeling of confusion and inadequacy. This anxiety frequently stems from the fact that many students are unfamiliar and inexperienced with this genre of writing. Never fear—inexperience and unfamiliarity are situations you can change through practice! Writing a research paper is an essential aspect of academics and should not be avoided on account of one's anxiety. In fact, the process of writing a research paper can be one of the more rewarding experiences one may encounter in academics. What is more, many students will continue to do research throughout their careers, which is one of the reasons this topic is so important.

Becoming an experienced researcher and writer in any field or discipline takes a great deal of practice. There are few individuals for whom this process comes naturally. Remember, even the most seasoned academic veterans have had to learn how to write a research paper at some point in their career. Therefore, with diligence, organization, practice, a willingness to learn (and to make mistakes!), and, perhaps most important of all, patience, students will find that they can achieve great things through their research and writing.

The pages in this section cover the following topic areas related to the process of writing a research paper:

• Genre - This section will provide an overview for understanding the difference between an analytical and argumentative research paper.
• Choosing a Topic - This section will guide the student through the process of choosing topics, whether the topic be one that is assigned or one that the student chooses themselves.
• Identifying an Audience - This section will help the student understand the often times confusing topic of audience by offering some basic guidelines for the process.
• Where Do I Begin - This section concludes the handout by offering several links to resources at Purdue, and also provides an overview of the final stages of writing a research paper.

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Translated by members of the EpiMan Forum, coordinated by Qiguo Lian. Please note that the translation is the work of the authors and PLOS is not responsible for any inaccuracies.

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• v.18(6); 2022 Jun

Ten simple rules for good research practice

Simon schwab.

1 Center for Reproducible Science, University of Zurich, Zurich, Switzerland

2 Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland

Perrine Janiaud

3 Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland

Michael Dayan

4 Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland

Valentin Amrhein

5 Department of Environmental Sciences, Zoology, University of Basel, Basel, Switzerland

Radoslaw Panczak

6 Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland

Patricia M. Palagi

7 SIB Training Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland

Lars G. Hemkens

8 Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, United States of America

9 Meta-Research Innovation Center Berlin (METRIC-B), Berlin Institute of Health, Berlin, Germany

Meike Ramon

10 Applied Face Cognition Lab, University of Lausanne, Lausanne, Switzerland

Nicolas Rothen

11 Faculty of Psychology, UniDistance Suisse, Brig, Switzerland

Stephen Senn

12 Statistical Consultant, Edinburgh, United Kingdom

Leonhard Held

This is a PLOS Computational Biology Methods paper.

Introduction

The lack of research reproducibility has caused growing concern across various scientific fields [ 1 – 5 ]. Today, there is widespread agreement, within and outside academia, that scientific research is suffering from a reproducibility crisis [ 6 , 7 ]. Researchers reach different conclusions—even when the same data have been processed—simply due to varied analytical procedures [ 8 , 9 ]. As we continue to recognize this problematic situation, some major causes of irreproducible research have been identified. This, in turn, provides the foundation for improvement by identifying and advocating for good research practices (GRPs). Indeed, powerful solutions are available, for example, preregistration of study protocols and statistical analysis plans, sharing of data and analysis code, and adherence to reporting guidelines. Although these and other best practices may facilitate reproducible research and increase trust in science, it remains the responsibility of researchers themselves to actively integrate them into their everyday research practices.

Contrary to ubiquitous specialized training, cross-disciplinary courses focusing on best practices to enhance the quality of research are lacking at universities and are urgently needed. The intersections between disciplines offer a space for peer evaluation, mutual learning, and sharing of best practices. In medical research, interdisciplinary work is inevitable. For example, conducting clinical trials requires experts with diverse backgrounds, including clinical medicine, pharmacology, biostatistics, evidence synthesis, nursing, and implementation science. Bringing researchers with diverse backgrounds and levels of experience together to exchange knowledge and learn about problems and solutions adds value and improves the quality of research.

The present selection of rules was based on our experiences with teaching GRP courses at the University of Zurich, our course participants’ feedback, and the views of a cross-disciplinary group of experts from within the Swiss Reproducibility Network ( www.swissrn.org ). The list is neither exhaustive, nor does it aim to address and systematically summarize the wide spectrum of issues including research ethics and legal aspects (e.g., related to misconduct, conflicts of interests, and scientific integrity). Instead, we focused on practical advice at the different stages of everyday research: from planning and execution to reporting of research. For a more comprehensive overview on GRPs, we point to the United Kingdom’s Medical Research Council’s guidelines [ 10 ] and the Swedish Research Council’s report [ 11 ]. While the discussion of the rules may predominantly focus on clinical research, much applies, in principle, to basic biomedical research and research in other domains as well.

The 10 proposed rules can serve multiple purposes: an introduction for researchers to relevant concepts to improve research quality, a primer for early-career researchers who participate in our GRP courses, or a starting point for lecturers who plan a GRP course at their own institutions. The 10 rules are grouped according to planning (5 rules), execution (3 rules), and reporting of research (2 rules); see Fig 1 . These principles can (and should) be implemented as a habit in everyday research, just like toothbrushing.

GRP, good research practices.

Research planning

Rule 1: specify your research question.

Coming up with a research question is not always simple and may take time. A successful study requires a narrow and clear research question. In evidence-based research, prior studies are assessed in a systematic and transparent way to identify a research gap for a new study that answers a question that matters [ 12 ]. Papers that provide a comprehensive overview of the current state of research in the field are particularly helpful—for example, systematic reviews. Perspective papers may also be useful, for example, there is a paper with the title “SARS-CoV-2 and COVID-19: The most important research questions.” However, a systematic assessment of research gaps deserves more attention than opinion-based publications.

In the next step, a vague research question should be further developed and refined. In clinical research and evidence-based medicine, there is an approach called population, intervention, comparator, outcome, and time frame (PICOT) with a set of criteria that can help framing a research question [ 13 ]. From a well-developed research question, subsequent steps will follow, which may include the exact definition of the population, the outcome, the data to be collected, and the sample size that is required. It may be useful to find out if other researchers find the idea interesting as well and whether it might promise a valuable contribution to the field. However, actively involving the public or the patients can be a more effective way to determine what research questions matter.

The level of details in a research question also depends on whether the planned research is confirmatory or exploratory. In contrast to confirmatory research, exploratory research does not require a well-defined hypothesis from the start. Some examples of exploratory experiments are those based on omics and multi-omics experiments (genomics, bulk RNA-Seq, single-cell, etc.) in systems biology and connectomics and whole-brain analyses in brain imaging. Both exploration and confirmation are needed in science, and it is helpful to understand their strengths and limitations [ 14 , 15 ].

Rule 2: Write and register a study protocol

In clinical research, registration of clinical trials has become a standard since the late 1990 and is now a legal requirement in many countries. Such studies require a study protocol to be registered, for example, with ClinicalTrials.gov, the European Clinical Trials Register, or the World Health Organization’s International Clinical Trials Registry Platform. Similar effort has been implemented for registration of systematic reviews (PROSPERO). Study registration has also been proposed for observational studies [ 16 ] and more recently in preclinical animal research [ 17 ] and is now being advocated across disciplines under the term “preregistration” [ 18 , 19 ].

Study protocols typically document at minimum the research question and hypothesis, a description of the population, the targeted sample size, the inclusion/exclusion criteria, the study design, the data collection, the data processing and transformation, and the planned statistical analyses. The registration of study protocols reduces publication bias and hindsight bias and can safeguard honest research and minimize waste of research [ 20 – 22 ]. Registration ensures that studies can be scrutinized by comparing the reported research with what was actually planned and written in the protocol, and any discrepancies may indicate serious problems (e.g., outcome switching).

Note that registration does not mean that researchers have no flexibility to adapt the plan as needed. Indeed, new or more appropriate procedures may become available or known only after registration of a study. Therefore, a more detailed statistical analysis plan can be amended to the protocol before the data are observed or unblinded [ 23 , 24 ]. Likewise, registration does not exclude the possibility to conduct exploratory data analyses; however, they must be clearly reported as such.

To go even further, registered reports are a novel article type that incentivize high-quality research—irrespective of the ultimate study outcome [ 25 , 26 ]. With registered reports, peer-reviewers decide before anyone knows the results of the study, and they have a more active role in being able to influence the design and analysis of the study. Journals from various disciplines increasingly support registered reports [ 27 ].

Naturally, preregistration and registered reports also have their limitations and may not be appropriate in a purely hypothesis-generating (explorative) framework. Reports of exploratory studies should indeed not be molded into a confirmatory framework; appropriate rigorous reporting alternatives have been suggested and start to become implemented [ 28 , 29 ].

Rule 3: Justify your sample size

Early-career researchers in our GRP courses often identify sample size as an issue in their research. For example, they say that they work with a low number of samples due to slow growth of cells, or they have a limited number of patient tumor samples due to a rare disease. But if your sample size is too low, your study has a high risk of providing a false negative result (type II error). In other words, you are unlikely to find an effect even if there truly was an effect.

Unfortunately, there is more bad news with small studies. When an effect from a small study was selected for drawing conclusions because it was statistically significant, low power increases the probability that an effect size is overestimated [ 30 , 31 ]. The reason is that with low power, studies that due to sampling variation find larger (overestimated) effects are much more likely to be statistically significant than those that happen to find smaller (more realistic) effects [ 30 , 32 , 33 ]. Thus, in such situations, effect sizes are often overestimated. For the phenomenon that small studies often report more extreme results (in meta-analyses), the term “small-study effect” was introduced [ 34 ]. In any case, an underpowered study is a problematic study, no matter the outcome.

In conclusion, small sample sizes can undermine research, but when is a study too small? For one study, a total of 50 patients may be fine, but for another, 1,000 patients may be required. How large a study needs to be designed requires an appropriate sample size calculation. Appropriate sample size calculation ensures that enough data are collected to ensure sufficient statistical power (the probability to reject the null hypothesis when it is in fact false).

Low-powered studies can be avoided by performing a sample size calculation to find out the required sample size of the study. This requires specifying a primary outcome variable and the magnitude of effect you are interested in (among some other factors); in clinical research, this is often the minimal clinically relevant difference. The statistical power is often set at 80% or larger. A comprehensive list of packages for sample size calculation are available [ 35 ], among them the R package “pwr” [ 36 ]. There are also many online calculators available, for example, the University of Zurich’s “SampleSizeR” [ 37 ].

A worthwhile alternative for planning the sample size that puts less emphasis on null hypothesis testing is based on the desired precision of the study; for example, one can calculate the sample size that is necessary to obtain a desired width of a confidence interval for the targeted effect [ 38 – 40 ]. A general framework to sample size justification beyond a calculation-only approach has been proposed [ 41 ]. It is also worth mentioning that some study types have other requirements or need specific methods. In diagnostic testing, one would need to determine the anticipated minimal sensitivity or specificity; in prognostic research, the number of parameters that can be used to fit a prediction model given a fixed sample size should be specified. Designs can also be so complex that a simulation (Monte Carlo method) may be required.

Sample size calculations should be done under different assumptions, and the largest estimated sample size is often the safer bet than a best-case scenario. The calculated sample size should further be adjusted to allow for possible missing data. Due to the complexity of accurately calculating sample size, researchers should strongly consider consulting a statistician early in the study design process.

Rule 4: Write a data management plan

In 2020, 2 Coronavirus Disease 2019 (COVID-19) papers in leading medical journals were retracted after major concerns about the data were raised [ 42 ]. Today, raw data are more often recognized as a key outcome of research along with the paper. Therefore, it is important to develop a strategy for the life cycle of data, including suitable infrastructure for long-term storage.

The data life cycle is described in a data management plan: a document that describes what data will be collected and how the data will be organized, stored, handled, and protected during and after the end of the research project. Several funders require a data management plan in grant submissions, and publishers like PLOS encourage authors to do so as well. The Wellcome Trust provides guidance in the development of a data management plan, including real examples from neuroimaging, genomics, and social sciences [ 43 ]. However, projects do not always allocate funding and resources to the actual implementation of the data management plan.

The Findable, Accessible, Interoperable, and Reusable (FAIR) data principles promote maximal use of data and enable machines to access and reuse data with minimal human intervention [ 44 ]. FAIR principles require the data to be retained, preserved, and shared preferably with an immutable unique identifier and a clear usage license. Appropriate metadata will help other researchers (or machines) to discover, process, and understand the data. However, requesting researchers to fully comply with the FAIR data principles in every detail is an ambitious goal.

Multidisciplinary data repositories that support FAIR are, for example, Dryad (datadryad.org https://datadryad.org/ ), EUDAT ( www.eudat.eu ), OSF (osf.io https://osf.io/ ), and Zenodo (zenodo.org https://zenodo.org/ ). A number of institutional and field-specific repositories may also be suitable. However, sometimes, authors may not be able to make their data publicly available for legal or ethical reasons. In such cases, a data user agreement can indicate the conditions required to access the data. Journals highlight what are acceptable and what are unacceptable data access restrictions and often require a data availability statement.

Organizing the study artifacts in a structured way greatly facilitates the reuse of data and code within and outside the lab, enhancing collaborations and maximizing the research investment. Support and courses for data management plans are sometimes available at universities. Another 10 simple rules paper for creating a good data management plan is dedicated to this topic [ 45 ].

Rule 5: Reduce bias

Bias is a distorted view in favor of or against a particular idea. In statistics, bias is a systematic deviation of a statistical estimate from the (true) quantity it estimates. Bias can invalidate our conclusions, and the more bias there is, the less valid they are. For example, in clinical studies, bias may mislead us into reaching a causal conclusion that the difference in the outcomes was due to the intervention or the exposure. This is a big concern, and, therefore, the risk of bias is assessed in clinical trials [ 46 ] as well as in observational studies [ 47 , 48 ].

There are many different forms of bias that can occur in a study, and they may overlap (e.g., allocation bias and confounding bias) [ 49 ]. Bias can occur at different stages, for example, immortal time bias in the design of the study, information bias in the execution of the study, and publication bias in the reporting of research. Understanding bias allows us researchers to remain vigilant of potential sources of bias when peer-reviewing and designing own studies. We summarized some common types of bias and some preventive steps in Table 1 , but many other forms of bias exist; for a comprehensive overview, see the Oxford University’s Catalogue of Bias [ 50 ].

For a comprehensive collection, see catalogofbias.org .

Here are some noteworthy examples of study bias from the literature: An example of information bias was observed when in 1998 an alleged association between the measles, mumps, and rubella (MMR) vaccine and autism was reported. Recall bias (a subtype of information bias) emerged when parents of autistic children recalled the onset of autism after an MMR vaccination more often than parents of similar children who were diagnosed prior to the media coverage of that controversial and meanwhile retracted study [ 51 ]. A study from 2001 showed better survival for academy award-winning actors, but this was due to immortal time bias that favors the treatment or exposure group [ 52 , 53 ]. A study systematically investigated self-reports about musculoskeletal symptoms and found the presence of information bias. The reason was that participants with little computer-time overestimated, and participants with a lot of computer-time spent underestimated their computer usage [ 54 ].

Information bias can be mitigated by using objective rather than subjective measurements. Standardized operating procedures (SOP) and electronic lab notebooks additionally help to follow well-designed protocols for data collection and handling [ 55 ]. Despite the failure to mitigate bias in studies, complete descriptions of data and methods can at least allow the assessment of risk of bias.

Research execution

Rule 6: avoid questionable research practices.

Questionable research practices (QRPs) can lead to exaggerated findings and false conclusions and thus lead to irreproducible research. Often, QRPs are used with no bad intentions. This becomes evident when methods sections explicitly describe such procedures, for example, to increase the number of samples until statistical significance is reached that supports the hypothesis. Therefore, it is important that researchers know about QRPs in order to recognize and avoid them.

Several questionable QRPs have been named [ 56 , 57 ]. Among them are low statistical power, pseudoreplication, repeated inspection of data, p -hacking [ 58 ], selective reporting, and hypothesizing after the results are known (HARKing).

The first 2 QRPs, low statistical power and pseudoreplication, can be prevented by proper planning and designing of studies, including sample size calculation and appropriate statistical methodology to avoid treating data as independent when in fact they are not. Statistical power is not equal to reproducibility, but statistical power is a precondition of reproducibility as the lack thereof can result in false negative as well as false positive findings (see Rule 3 ).

In fact, a lot of QRP can be avoided with a study protocol and statistical analysis plan. Preregistration, as described in Rule 2, is considered best practice for this purpose. However, many of these issues can additionally be rooted in institutional incentives and rewards. Both funding and promotion are often tied to the quantity rather than the quality of the research output. At universities, still only few or no rewards are given for writing and registering protocols, sharing data, publishing negative findings, and conducting replication studies. Thus, a wider “culture change” is needed.

Rule 7: Be cautious with interpretations of statistical significance

It would help if more researchers were familiar with correct interpretations and possible misinterpretations of statistical tests, p -values, confidence intervals, and statistical power [ 59 , 60 ]. A statistically significant p -value does not necessarily mean that there is a clinically or biologically relevant effect. Specifically, the traditional dichotomization into statistically significant ( p < 0.05) versus statistically nonsignificant ( p ≥ 0.05) results is seldom appropriate, can lead to cherry-picking of results and may eventually corrupt science [ 61 ]. We instead recommend reporting exact p -values and interpreting them in a graded way in terms of the compatibility of the null hypothesis with the data [ 62 , 63 ]. Moreover, a p -value around 0.05 (e.g., 0.047 or 0.055) provides only little information, as is best illustrated by the associated replication power: The probability that a hypothetical replication study of the same design will lead to a statistically significant result is only 50% [ 64 ] and is even lower in the presence of publication bias and regression to the mean (the phenomenon that effect estimates in replication studies are often smaller than the estimates in the original study) [ 65 ]. Claims of novel discoveries should therefore be based on a smaller p -value threshold (e.g., p < 0.005) [ 66 ], but this really depends on the discipline (genome-wide screenings or studies in particle physics often apply much lower thresholds).

Generally, there is often too much emphasis on p -values. A statistical index such as the p -value is just the final product of an analysis, the tip of the iceberg [ 67 ]. Statistical analyses often include many complex stages, from data processing, cleaning, transformation, addressing missing data, modeling, to statistical inference. Errors and pitfalls can creep in at any stage, and even a tiny error can have a big impact on the result [ 68 ]. Also, when many hypothesis tests are conducted (multiple testing), false positive rates may need to be controlled to protect against wrong conclusions, although adjustments for multiple testing are debated [ 69 – 71 ].

Thus, a p -value alone is not a measure of how credible a scientific finding is [ 72 ]. Instead, the quality of the research must be considered, including the study design, the quality of the measurement, and the validity of the assumptions that underlie the data analysis [ 60 , 73 ]. Frameworks exist that help to systematically and transparently assess the certainty in evidence; the most established and widely used one is Grading of Recommendations, Assessment, Development and Evaluations (GRADE; www.gradeworkinggroup.org ) [ 74 ].

Training in basic statistics, statistical programming, and reproducible analyses and better involvement of data professionals in academia is necessary. University departments sometimes have statisticians that can support researchers. Importantly, statisticians need to be involved early in the process and on an equal footing and not just at the end of a project to perform the final data analysis.

Rule 8: Make your research open

In reality, science often lacks transparency. Open science makes the process of producing evidence and claims transparent and accessible to others [ 75 ]. Several universities and research funders have already implemented open science roadmaps to advocate free and public science as well as open access to scientific knowledge, with the aim of further developing the credibility of research. Open research allows more eyes to see it and critique it, a principle similar to the “Linus’s law” in software development, which says that if there are enough people to test a software, most bugs will be discovered.

As science often progresses incrementally, writing and sharing a study protocol and making data and methods readily available is crucial to facilitate knowledge building. The Open Science Framework (osf.io) is a free and open-source project management tool that supports researchers throughout the entire project life cycle. OSF enables preregistration of study protocols and sharing of documents, data, analysis code, supplementary materials, and preprints.

To facilitate reproducibility, a research paper can link to data and analysis code deposited on OSF. Computational notebooks are now readily available that unite data processing, data transformations, statistical analyses, figures and tables in a single document (e.g., R Markdown, Jupyter); see also the 10 simple rules for reproducible computational research [ 76 ]. Making both data and code open thus minimizes waste of funding resources and accelerates science.

Open science can also advance researchers’ careers, especially for early-career researchers. The increased visibility, retrievability, and citations of datasets can all help with career building [ 77 ]. Therefore, institutions should provide necessary training, and hiring committees and journals should align their core values with open science, to attract researchers who aim for transparent and credible research [ 78 ].

Research reporting

Rule 9: report all findings.

Publication bias occurs when the outcome of a study influences the decision whether to publish it. Researchers, reviewers, and publishers often find nonsignificant study results not interesting or worth publishing. As a consequence, outcomes and analyses are only selectively reported in the literature [ 79 ], also known as the file drawer effect [ 80 ].

The extent of publication bias in the literature is illustrated by the overwhelming frequency of statistically significant findings [ 81 ]. A study extracted p -values from MEDLINE and PubMed Central and showed that 96% of the records reported at least 1 statistically significant p -value [ 82 ], which seems implausible in the real world. Another study plotted the distribution of more than 1 million z -values from Medline, revealing a huge gap from −2 to 2 [ 83 ]. Positive studies (i.e., statistically significant, perceived as striking or showing a beneficial effect) were 4 times more likely to get published than negative studies [ 84 ].

Often a statistically nonsignificant result is interpreted as a “null” finding. But a nonsignificant finding does not necessarily mean a null effect; absence of evidence is not evidence of absence [ 85 ]. An individual study may be underpowered, resulting in a nonsignificant finding, but the cumulative evidence from multiple studies may indeed provide sufficient evidence in a meta-analysis. Another argument is that a confidence interval that contains the null value often also contains non-null values that may be of high practical importance. Only if all the values inside the interval are deemed unimportant from a practical perspective, then it may be fair to describe a result as a null finding [ 61 ]. We should thus never report “no difference” or “no association” just because a p -value is larger than 0.05 or, equivalently, because a confidence interval includes the “null” [ 61 ].

On the other hand, studies sometimes report statistically nonsignificant results with “spin” to claim that the experimental treatment is beneficial, often by focusing their conclusions on statistically significant differences on secondary outcomes despite a statistically nonsignificant difference for the primary outcome [ 86 , 87 ].

Findings that are not being published have a tremendous impact on the research ecosystem, distorting our knowledge of the scientific landscape by perpetuating misconceptions, and jeopardizing judgment of researchers and the public trust in science. In clinical research, publication bias can mislead care decisions and harm patients, for example, when treatments appear useful despite only minimal or even absent benefits reported in studies that were not published and thus are unknown to physicians [ 88 ]. Moreover, publication bias also directly affects the formulation and proliferation of scientific theories, which are taught to students and early-career researchers, thereby perpetuating biased research from the core. It has been shown in modeling studies that unless a sufficient proportion of negative studies are published, a false claim can become an accepted fact [ 89 ] and the false positive rates influence trustworthiness in a given field [ 90 ].

In sum, negative findings are undervalued. They need to be more consistently reported at the study level or be systematically investigated at the systematic review level. Researchers have their share of responsibilities, but there is clearly a lack of incentives from promotion and tenure committees, journals, and funders.

Rule 10: Follow reporting guidelines

Study reports need to faithfully describe the aim of the study and what was done, including potential deviations from the original protocol, as well as what was found. Yet, there is ample evidence of discrepancies between protocols and research reports, and of insufficient quality of reporting [ 79 , 91 – 95 ]. Reporting deficiencies threaten our ability to clearly communicate findings, replicate studies, make informed decisions, and build on existing evidence, wasting time and resources invested in the research [ 96 ].

Reporting guidelines aim to provide the minimum information needed on key design features and analysis decisions, ensuring that findings can be adequately used and studies replicated. In 2008, the Enhancing the QUAlity and Transparency Of Health Research (EQUATOR) network was initiated to provide reporting guidelines for a variety of study designs along with guidelines for education and training on how to enhance quality and transparency of health research. Currently, there are 468 reporting guidelines listed in the network; see the most prominent guidelines in Table 2 . Furthermore, following the ICMJE recommendations, medical journals are increasingly endorsing reporting guidelines [ 97 ], in some cases making it mandatory to submit the appropriate reporting checklist along with the manuscript.

The EQUATOR Network is a library with more than 400 reporting guidelines in health research ( www.equator-network.org ).

The use of reporting guidelines and journal endorsement has led to a positive impact on the quality and transparency of research reporting, but improvement is still needed to maximize the value of research [ 98 , 99 ].

Conclusions

Originally, this paper targeted early-career researchers; however, throughout the development of the rules, it became clear that the present recommendations can serve all researchers irrespective of their seniority. We focused on practical guidelines for planning, conducting, and reporting of research. Others have aligned GRP with similar topics [ 100 , 101 ]. Even though we provide 10 simple rules, the word “simple” should not be taken lightly. Putting the rules into practice usually requires effort and time, especially at the beginning of a research project. However, time can also be redeemed, for example, when certain choices can be justified to reviewers by providing a study protocol or when data can be quickly reanalyzed by using computational notebooks and dynamic reports.

Researchers have field-specific research skills, but sometimes are not aware of best practices in other fields that can be useful. Universities should offer cross-disciplinary GRP courses across faculties to train the next generation of scientists. Such courses are an important building block to improve the reproducibility of science.

Acknowledgments

This article was written along the Good Research Practice (GRP) courses at the University of Zurich provided by the Center of Reproducible Science ( www.crs.uzh.ch ). All materials from the course are available at https://osf.io/t9rqm/ . We appreciated the discussion, development, and refinement of this article within the working group “training” of the SwissRN ( www.swissrn.org ). We are grateful to Philip Bourne for a lot of valuable comments on the earlier versions of the manuscript.

Funding Statement

S.S. received funding from SfwF (Stiftung für wissenschaftliche Forschung an der Universität Zürich; grant no. STWF-19-007). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

• Sep 16, 2019
• 11 min read

Guidelines and Rules for Presenting Numbers in Research Papers

Updated: May 7, 2020

Since numbers are at the heart of research, you should know common rules regarding presenting numbers representing quantitative data in research papers. Knowing these rules will be helpful for writing the material and method section as well as other sections of the paper. If you are aiming to publish in a scientific or scholarly journal, you should check the Guidelines for Authors page of the journal you are targeting for the specific style guide that they follow. Since there are some variations found in different style guides, this will be important to know which guide they adopt. If they do not give this sort of information, it can be helpful to follow some common guidelines prescribed from respected sources like the Council of Scientific Editors. For more detailed coverage of presenting numbers, statistics and mathematical equations in research papers check out: Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers, The Chicago Manual of Style, and How to Report Statistics in Medicine. My apologies for instances where certain math characters were lost in copying below, specifically those related to exponents and superscript in scientific notation.

1. In scientific and technical texts, with a focus on quantitative data, represent a number with its numeral form, not word form:

312 base pairs

2. Use the numeral form when comparing with numbers:

A total of 5 out of 24 of the respondents dropped out of the study.

NOT: A total of five out of twenty four of the respondents dropped out of the study.

3. Do not begin a sentence with a digit; instead use the word form for the number in question, even if it is above eleven:

Fifty-six rats were used.

NOT: 56 rats were used.

Or rewrite the sentence instead of beginning with a lengthy word:

A total of 4,589 moths were collected.

NOT: Four thousand five hundred eighty-nine moths were collected.

4. Separate every three digits with a comma, except with numbers after a decimal. Use a period as a decimal point, and not a comma:

3,000 participants completed the survey.

NOT: 3.000 participants completed the survey.

5. Be careful with compound nouns that report numbers. All words preceding the head noun must be singular since they function like adjectives. In English, adjectives are always singular:

A 36-day-old rat.

NOT: a 36 days old rat.

6. The terms twice vs. two times have essentially the same meaning, except that twice might be favored for being shorter.

The specimens were disrupted by sonication two times for 45 s at 5°C.

The specimens were disrupted by sonication twice for 45 s at 5°C.

7. The term circa is used with historical dates, but not typically with measurements. Likewise, the symbol, “” means approximately. Only use it in math applications, not in prose. Instead, use the word “approximately” in running text:

The temple was destroyed circa 1432 BCE.

Approximately 542 birds were sighted.

NOT: Circa 542 birds were sighted.

Approximately 2ml was added to the buffer.

NOT: Circa 2ml was added to the buffer.

The temperature was approximately 35C

NOT: The temperature was “” 35

8. Avoid imprecise expressions such as a 3-fold rise, 2-fold increase, two times as much , but instead use a more precise numerical percentage or decimal point when reporting precise quantities. This form can be used in a context where an approximation is acceptable, yet the number form should be used, not the word form:

3-fold increase NOT: threefold increase

9. When describing a decade use this form:

In the 1970s

During the 1980s

NOT: In the 70’s

NOT: In the Seventies

NOT: I n the 70s

10. Ordinals are commonly used in English to focus on rank, order or a sequence of certain quantitative data. They can be represented in numerical form or word form; for example, 1st, 2nd, 3rd, 4th, first, second third, and fourth. Do not confuse their form:

Eleventh, twelfth, thirteenth,…

NOT: eleventeen, twelveteen,…

As the CSE points out, “Ordinal numbers generally convey rank order, not quantity. Rather than being expressly enumerative (answering the question “How many?”), ordinals often describe “which”, “what”, or “in what sequence”. Because this function of ordinals is more prose-oriented than quantitative, distinctiveness within the text is less important for ordinal numbers, and undisrupted reading flow and comprehension take precedence”. Hence use the word form for ordinal numbers under 10:

The second wave toppled the wall.

The third sample contained only sediment.

The ninth patient quit the study due to family issues.

Use the numeric form for larger numbers above 10 as the word forms can be lengthy and awkward:

The 15th attempt was successful.

The 25th test was incomplete.

We focused on the 19th century.

The 97th test run

NOT: The ninety-seventh test run

The 21st Century

NOT: twenty-first Century

The numeric form can be used for numbers under 10 if they referred to repeatedly:

We surveyed 8 subjects: the 1st was most coherent, the 3rd, 4th, and 6th were contradictory, while the 5th, 7th, and 8th were moderately coherent; yet t he 1st could not recall the incident, and the 6th and 8th provided highly specific details of certain events.

Do not use an ordinal when writing the complete date:

February 7, 2014.

NOT: February 7th, 2014.

Use the short numerical form rather than the longer word form when discussing centuries:

Then 19thCentury

NOT: The nineteenth Century

11. Use the percent symbol (%) whenever a numeral accompanies it. Also, use no space between the number and the percent symbol:

NOT: 0.053 percent

NOT: 0.053 %

12. When two numbers are adjacent, for the sake of readability, spell out one and leave the other as a numerical form:

As shown in Table 2, three were not recovered.

NOT: As shown in Table 2, 3 were not recovered.

13. In running text in general, fractions should be represented in word form, rather than numerals. All two-word fractions should be hyphenated, whether as a noun or adjective form.

Roughly one-tenth of the study subjects reported adverse effects.

Two-thirds of this species is found in Brazil.

Nearly three-quarters of the respondents were pleased with the outcome .

Yet, for fraction quantities greater than one, use mixed fractions when you do not intend to give a precise value:

The study site was approximately 3¾ kilometers from the river.

The study ran for about 2½ years.

When a more precise value is desired, use a percentage or decimal form of the number.For mixed numbers with built up fractions, place the whole number close to the fraction, but for solid fractions, place a space between the whole number and the fraction:

Built up fraction: 9

Solid fractions: 9 2/3

14. With numbers that are less than 1.0, use an initial zero to the left of the decimal point:

0.345 NOT: .345

NOT: P = .05

15. When reporting quantities, consider what unit of measurement and decimal place is most meaningful to report. Round numbers to the most relevant and meaningful digit. For example, while reporting the average length of a group of fish, reporting centimeters would be the most meaningful unit to report. For example, it would be meaningful to report an average length of fish as 12 cm, and it might even be meaningful to report the tenths of Cen termers as in 12.4 cm, yet it would not be necessary to report in hundreds 12.37 cm or thousands of centimeters as in 12.372 cm. Reporting too many decimal points can be distracting to the reader and have little scientific importance. For example, note how it is easy to grasp the general pattern of weight gain in the following two sentences:

We noticed an average weight gain of 14.4529 g for college students, 12.39815 g for retired couples and 2.99277 g for single parents.

We noticed an average weight gain of 14 g for college students, 12 g for retired couples and 3g for single parents.

16. When reporting percentages, if the sample you are considering is less than 100, then round to whole numbers. With samples larger than 100, it could be meaningful to report one decimal point. Yet, consider how it will improve the readability and importance of the number. Note this pattern in the sentences below:

Of the 23 students studied, 32% (7 students) reacted favorably, 49% (11 students) had a neutral response, and 19% (4 students) had an adverse reaction to the practice.

NOT: Of the 23 students studied, 32.432% (7 students) reacted favorably, 48.983% (11 students) had a neutral response, and 18.594% (4 students) had an adverse reaction to the practice.

17. In research papers, numbers typically combine with units of measure or symbols, as specified and defined by the International System of Units (Système International d’Unités). These symbols can be alphabetical ( e.g., kg, μg, K, mol, A, s, Hz, mm, mL, min, g, cm) or non-alphabetical (e.g., $, %, S, £, °, ¹). As a general rule, numerals should always accompany these symbols:

A 25.0 mL  aliquot of 0.25 M HCNO (weak acid) is titrated with 0.15 M NaOH.

Near lead smelters and battery plants, air levels typically ranged from 0.3 to 4.0 μg/m3

18. Separate symbols from numbers with a single space:

19. Close up the space between a non alphabetical symbol and a number:

Note, one exception to this rule: The Council of Scientific Editors recommend a space here, while the American Medical Association recommends no space:

CSE Style: 45 °C

AMA Style: 45°C

Ultimately, you will need to follow the style guide recommendations from the journal that you planning to submit your research paper to.

21. When representing numbers in a range, use the word “to” between numbers, and not a hyphen or a dash:

Regional unemployment rates ranged from 1.2% to 33.3%.

NOT: Regional unemployment rates ranged from 1.2% - 33.3%.

When using the preposition “between” to introduce a range, always accompany it with “and”, not a hyphen or a dash:

In a range between 4 and 10cm.

NOT: In a range between 4 - 10cm.

When the range includes numbers with several digits, do not leave out the leading numbers of the second number of the range:

1958 to 1962

NOT: 1958 to 62

1,724 to 1,736

NOT: 1,724 to 36

You can use a single unit symbol alone after second number in a range of numbers, except for when the symbol is non-alphabetical and must be closed up to the number (e.g., $,%).

30 to 45 mL

120 to 200 Hz

10 to 20 min

NOT: 40 to $60

NOT: 13 to 22%

Be careful when expressing a change in value in a range, especially when using terms like “increased”, “decreased” or “changed”. Use language that clarifies that the change is in the range or in the final amount.

Growth increased by a range of 1.5 g/d to 3.5 g/d.

Growth increased from an initial value a range of 1.5 g/d to a final value of 3.5 g/d.

NOT: Growth increased by 1.5 g/d to 3.5 g/d.

NOT: Growth increased from 1.5 g/d to 3.5 g/d.

22. When reporting dimensions, use a multiplication symbol and not the letter “x” or the word “by”, and leave a space between the multiplication symbol and the numbers:

NOT: 22 by 18 by 16

When the focus is on expressing one range changing to a new range, place a hyphen between numbers to improve readability:

increased from 25–34 mm to 28–42 mm 

NOT:  increased from 25 to 34 mm to 28 to 42 mm

23. For a series of numbers, place the symbol after the last number, except in cases where the symbol must be close to a number:

14, 15, 18, and 54 Hz

$21, $37, and $41

10%, 14% and 34%

24. Express large numbers or very small number in powers of 10, scientific notation.

NOT: 38,000

NOT: 735,000,000

NOT: 0.000,003,51

25. For large numbers that are not expressing high precision, a combination of numbers and words are acceptable:

The population is around 25 million.

NOT: The population is around 25, 000, 000.

26. With common symbols of math operations ( separate the symbol and number with a space or thin space. Use the math symbol and not the letter x to represent multiplication. Do not use these sybmols in running text:

The averages equaled the total of all samples from plot A plus plot B.

NOT: The averages = the total of all samples from plot A + plot B.

When these symbols are used as modifiers of words, then close up the space between them and the term they modify. Also, do not place two or more operator symbols side by side.

Also, do not place two or more operator symbols side by side.

The total was greater than

NOT: The total was

27. For symbols used in calculus, refer to the Association of American Publishers for extensive details directions on their markup in manuscripts. For details on how to present vectors, scalars, tensors, matrices and determinants, see Scientific Style & Format: The Council of Scientific Editors, Chapter 12.

28. Brackets, parentheses, and braces in mathematics are referred to as enclosures or “fences”. In math, their order of use is parentheses within brackets within braces, and the reverse is order follows in non-mathematical prose: braces within brackets within parentheses.

mathematics: { [ ( ) ] }

prose or non-mathematics: ( [ {} ] )

29. In the following math expressions no space (closed up to the number) is required:

When expressing multiplication without the multiplication symbol:

Between fences and enclosures and the variables on either side of them:

(2p − 6bc)(1 − a)

 Between terms and their subscripts as in the following terms:

With the symbols plus and minus when used to indicate positive or negative value for numbers:

When expressing a ratio using a colon, close up the space:

Place a space between all common math operators: +, =, -,

30. Ratios, percentages, and proportions are commonly used to simplify and report research findings. Whenever using them, be sure to report a numerator and denominator of that accompanies them; otherwise it will be difficult to interpret them in a meaningful way. For instance 50% could be 2 of 4 samples had a positive result or 6,000 of 12,000 had a positive result. While both are examples of 50%, they would have a very different meaning in research. Separate the two numbers of a ratio by a colon, with the first typically being the numerator and the second the denominator:

The ratio of negative results was 3 to1 (946:329).

NOT: The ratio of negative results was 3 to1.

Proportions are the result of dividing the numerator by the denominator, with the numerator typically a subset of the items in the denominator:

The proportion of subjects experiencing adverse effects was 0.032 (21/651).

NOT: The proportion of subjects experiencing adverse effects was 0.032 .

To express a proportion as a percentage, multiply it by 100.

The percentage of subjects experiencing adverse effects 3.2% (21/651).

NOT: The percentage of subjects experiencing adverse effects 3.2% (21/651).

After studying the points made above about presenting numbers, correct the sentences below with errors related to numbers.

1. 4 assays were performed.

2. Measurements were made for just about one hundred and fifty snakes.

3. Since 80ies’ it has been shown that X plays a role in Y.

4. The 2th and 3th samples were negative.

5. This accounted for most of the total biomass.

6. Many informations can be found in the literature.

7. A lot of water was needed.

8. The deprotonated ion increased by about 2-fold.

9. For this case, the factor was just about 0.90, i.e. very close to one.

10. Three of percent of the samples were positive.

11. Each stock was valued at ten thousands of dollars.

12. Circa 10 mM was used.

13. 17x4=68

15. The total was

16. The population is around 25, 000, 000.

17. We found 15 % similarity.

18. The range increased from 25 to 34 mm to 28 to 42 mm.

19. As shown in table 3, 2 there was a significant increase.

20. The average cost per sample was 40 to $60

21. As many as 13 to 22% of the participants expreienced no adverse effect.

22. One tenth of the subjects reported improved vision.

23. We detected a difference of 0.000,003,51.

24. Statistical significance was set at .05

25. Rates ranged from 1.2% to 33.3%.

Check Answers Below:

Four assays were performed. Begin a sentence with the word form (four), not a digit (4). Measurements were taken for approximately 150 snakes. Since the 1980sit has been shown that X causes Y. The 2nd and 3rd were negative for… …Accounted for the majority of the biomass.a great deal of informationcan be found in the literature.A great deal of water was needed. Give a precise numerical percentage rather than something vague like “about 2-fold”.Avoid vague and informal term such as “just about” and “very close to”. Instead substitute “approximately” and “nearly”. Three percent of the samples were positive. Each stock was valued at ten-thousand dollars Approximately10 mM was used. (Use space between common math operators) 94 (use no space between numeral and exponent)The total was greater than (Avoid presenting two math operator symbols side by side).The population is around 25 million. (Use the word form when giving large imprecise numbers).We found 15% similarity. (No space between numerals and non-alphabetical symbols).The range increased from 25–34 mm to 28–42 mm. (When reporting a change of ranges, use a hyphen between numbers to improve readability).As shown in Table 3, three subjects dropped out. (When two numbers are adjacent, for the sake of readability, spell out one and leave the other as a numerical form).

20. The average cost per sample was $40 to $60 (When presenting a range, both numbers must be accompanied by the non-alphabetical symbol).

21. As many as 13% to 22% of the participants experienced no adverse effect. (When presenting a range, both numbers must be accompanied by the non-alphabetical symbol).

22. One-tenth of the subjects reported improved vision (hyphenate two-word fractions).

23. We detected a difference of 3.51 ´ 10-6 (write out very large or very small numbers in scientific notation)

24. Statistical significance was set at 0.05 (Place a zero before a decimal place.

25. Rates ranged from 1.2% to 33.3%. (Use the preposition “to” between numbers in a range, not a hyphen).

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• 15 April 2024
• Correction 22 April 2024

Revealed: the ten research papers that policy documents cite most

• Dalmeet Singh Chawla 0

Dalmeet Singh Chawla is a freelance science journalist based in London.

You can also search for this author in PubMed   Google Scholar

Policymakers often work behind closed doors — but the documents they produce offer clues about the research that influences them. Credit: Stefan Rousseau/Getty

When David Autor co-wrote a paper on how computerization affects job skill demands more than 20 years ago, a journal took 18 months to consider it — only to reject it after review. He went on to submit it to The Quarterly Journal of Economics , which eventually published the work 1 in November 2003.

Autor’s paper is now the third most cited in policy documents worldwide, according to an analysis of data provided exclusively to Nature . It has accumulated around 1,100 citations in policy documents, show figures from the London-based firm Overton (see ‘The most-cited papers in policy’), which maintains a database of more than 12 million policy documents, think-tank papers, white papers and guidelines.

“I thought it was destined to be quite an obscure paper,” recalls Autor, a public-policy scholar and economist at the Massachusetts Institute of Technology in Cambridge. “I’m excited that a lot of people are citing it.”

The most-cited papers in policy

Economics papers dominate the top ten papers that policy documents reference most.

Data from Overton as of 15 April 2024

The top ten most cited papers in policy documents are dominated by economics research; the number one most referenced study has around 1,300 citations. When economics studies are excluded, a 1997 Nature paper 2 about Earth’s ecosystem services and natural capital is second on the list, with more than 900 policy citations. The paper has also garnered more than 32,000 references from other studies, according to Google Scholar. Other highly cited non-economics studies include works on planetary boundaries, sustainable foods and the future of employment (see ‘Most-cited papers — excluding economics research’).

These lists provide insight into the types of research that politicians pay attention to, but policy citations don’t necessarily imply impact or influence, and Overton’s database has a bias towards documents published in English.

Interdisciplinary impact

Overton usually charges a licence fee to access its citation data. But last year, the firm worked with the publisher Sage to release a free web-based tool , based in Thousand Oaks, California, that allows any researcher to find out how many times policy documents have cited their papers or mention their names. Overton and Sage said they created the tool, called Sage Policy Profiles, to help researchers to demonstrate the impact or influence their work might be having on policy. This can be useful for researchers during promotion or tenure interviews and in grant applications.

Autor thinks his study stands out because his paper was different from what other economists were writing at the time. It suggested that ‘middle-skill’ work, typically done in offices or factories by people who haven’t attended university, was going to be largely automated, leaving workers with either highly skilled jobs or manual work. “It has stood the test of time,” he says, “and it got people to focus on what I think is the right problem.” That topic is just as relevant today, Autor says, especially with the rise of artificial intelligence.

Most-cited papers — excluding economics research

When economics studies are excluded, the research papers that policy documents most commonly reference cover topics including climate change and nutrition.

Walter Willett, an epidemiologist and food scientist at the Harvard T.H. Chan School of Public Health in Boston, Massachusetts, thinks that interdisciplinary teams are most likely to gain a lot of policy citations. He co-authored a paper on the list of most cited non-economics studies: a 2019 work 3 that was part of a Lancet commission to investigate how to feed the global population a healthy and environmentally sustainable diet by 2050 and has accumulated more than 600 policy citations.

“I think it had an impact because it was clearly a multidisciplinary effort,” says Willett. The work was co-authored by 37 scientists from 17 countries. The team included researchers from disciplines including food science, health metrics, climate change, ecology and evolution and bioethics. “None of us could have done this on our own. It really did require working with people outside our fields.”

Sverker Sörlin, an environmental historian at the KTH Royal Institute of Technology in Stockholm, agrees that papers with a diverse set of authors often attract more policy citations. “It’s the combined effect that is often the key to getting more influence,” he says.

Has your research influenced policy? Use this free tool to check

Sörlin co-authored two papers in the list of top ten non-economics papers. One of those is a 2015 Science paper 4 on planetary boundaries — a concept defining the environmental limits in which humanity can develop and thrive — which has attracted more than 750 policy citations. Sörlin thinks one reason it has been popular is that it’s a sequel to a 2009 Nature paper 5 he co-authored on the same topic, which has been cited by policy documents 575 times.

Although policy citations don’t necessarily imply influence, Willett has seen evidence that his paper is prompting changes in policy. He points to Denmark as an example, noting that the nation is reformatting its dietary guidelines in line with the study’s recommendations. “I certainly can’t say that this document is the only thing that’s changing their guidelines,” he says. But “this gave it the support and credibility that allowed them to go forward”.

Broad brush

Peter Gluckman, who was the chief science adviser to the prime minister of New Zealand between 2009 and 2018, is not surprised by the lists. He expects policymakers to refer to broad-brush papers rather than those reporting on incremental advances in a field.

Gluckman, a paediatrician and biomedical scientist at the University of Auckland in New Zealand, notes that it’s important to consider the context in which papers are being cited, because studies reporting controversial findings sometimes attract many citations. He also warns that the list is probably not comprehensive: many policy papers are not easily accessible to tools such as Overton, which uses text mining to compile data, and so will not be included in the database.

The top 100 papers

“The thing that worries me most is the age of the papers that are involved,” Gluckman says. “Does that tell us something about just the way the analysis is done or that relatively few papers get heavily used in policymaking?”

Gluckman says it’s strange that some recent work on climate change, food security, social cohesion and similar areas hasn’t made it to the non-economics list. “Maybe it’s just because they’re not being referred to,” he says, or perhaps that work is cited, in turn, in the broad-scope papers that are most heavily referenced in policy documents.

As for Sage Policy Profiles, Gluckman says it’s always useful to get an idea of which studies are attracting attention from policymakers, but he notes that studies often take years to influence policy. “Yet the average academic is trying to make a claim here and now that their current work is having an impact,” he adds. “So there’s a disconnect there.”

Willett thinks policy citations are probably more important than scholarly citations in other papers. “In the end, we don’t want this to just sit on an academic shelf.”

doi: https://doi.org/10.1038/d41586-024-00660-1

Updates & Corrections

Correction 22 April 2024 : The original version of this story credited Sage, rather than Overton, as the source of the policy papers’ citation data. Sage’s location has also been updated.

Autor, D. H., Levy, F. & Murnane, R. J. Q. J. Econ. 118 , 1279–1333 (2003).

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Costanza, R. et al. Nature 387 , 253–260 (1997).

Willett, W. et al. Lancet 393 , 447–492 (2019).

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Steffen, W. et al. Science 347 , 1259855 (2015).

Rockström, J. et al. Nature 461 , 472–475 (2009).

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Title: llm-r2: a large language model enhanced rule-based rewrite system for boosting query efficiency.

Abstract: Query rewrite, which aims to generate more efficient queries by altering a SQL query's structure without changing the query result, has been an important research problem. In order to maintain equivalence between the rewritten query and the original one during rewriting, traditional query rewrite methods always rewrite the queries following certain rewrite rules. However, some problems still remain. Firstly, existing methods of finding the optimal choice or sequence of rewrite rules are still limited and the process always costs a lot of resources. Methods involving discovering new rewrite rules typically require complicated proofs of structural logic or extensive user interactions. Secondly, current query rewrite methods usually rely highly on DBMS cost estimators which are often not accurate. In this paper, we address these problems by proposing a novel method of query rewrite named LLM-R2, adopting a large language model (LLM) to propose possible rewrite rules for a database rewrite system. To further improve the inference ability of LLM in recommending rewrite rules, we train a contrastive model by curriculum to learn query representations and select effective query demonstrations for the LLM. Experimental results have shown that our method can significantly improve the query execution efficiency and outperform the baseline methods. In addition, our method enjoys high robustness across different datasets.

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