proposal for statistical research project

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

• Introduction

Literature review

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Proposal Format

The proposal will usually have a  title page  that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

Introduction The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.. Your introduction should:

• Introduce your  topic
• Give necessary background and context
• Outline your  problem statement  and  research questions To guide your  introduction , include information about:  
• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights will your research contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong  literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or  synthesize  prior scholarship

Research design and methods

Following the literature review, restate your main  objectives . This brings the focus back to your project. Next, your  research design  or  methodology  section will describe your overall approach, and the practical steps you will take to answer your research questions. Write up your projected, if not actual, results.

Contribution to knowledge

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Lastly, your research proposal must include correct  citations  for every source you have used, compiled in a  reference list . To create citations quickly and easily, you can use free APA citation generators like BibGuru. Databases have a citation button you can click on to see your citation. Sometimes you have to re-format it as the citations may have mistakes. 

• << Previous: ProQuest Research Companion
• Next: DIR >>

Edit this Guide

Log into Dashboard

Use of RIT resources is reserved for current RIT students, faculty and staff for academic and teaching purposes only. Please contact your librarian with any questions.

Help is Available

Email a Librarian

A librarian is available by e-mail at [email protected]

Meet with a Librarian

Call reference desk voicemail.

A librarian is available by phone at (585) 475-2563 or on Skype at llll

Or, call (585) 475-2563 to leave a voicemail with the reference desk during normal business hours .

Chat with a Librarian

Data analytics resources infoguide url.

https://infoguides.rit.edu/DA

Use the box below to email yourself a link to this guide

• Submission Instructions
• Editorial Calendar
• 2009 Amstat News
• 2010 Amstat News
• 2011 Amstat News
• 2012 Amstat News
• 2013 Amstat News
• 2014 Amstat News
• 2015 Amstat News
• 2016 Amstat News
• 2017 Amstat News
• 2018 Amstat News
• 2019 Amstat News
• 2020 Amstat News
• 2021 Amstat News
• 2022 Amstat News
• 2023 Amstat News
• 2024 Amstat News
• Black History Month 2023
• Celebrating Women in Statistics 2022
• Black History Month 2022
• Celebrating Women in Statistics 2021
• Black History Month 2021
• Celebrating Hispanic Heritage Month 2020
• Celebrating Women in Statistics 2020
• Black History Month 2020
• Celebrating Women in Statistics 2018
• Celebrating Women in Statistics 2019

Tips for Writing a Statistical Analysis Plan

This column highlights research activities that may be of interest to asa members. this article includes information about new research solicitations and the federal budget for statistics. comments or suggestions for future articles may be sent to the amstat news managing editor at [email protected] ..

Contributing Editor Amy Herring is professor and associate chair of biostatistics at The University of North Carolina at Chapel Hill. She is PI of an R01 for developing statistical methods with applications in birth defects epidemiology and co-investigator on numerous projects in public health and medicine.

In the first of a series of articles commissioned by the ASA Committee on Funded Research , Jeremy Taylor provided an overview of the review process for statistical methodology grants in last month’s issue. This month, we consider important facets of writing statistical sections for NIH grants not primarily focused on development of new statistical methods. We assume readers are familiar with last month’s overview, particularly the description of the NIH, its review process, scoring of proposals, and other important issues.

In particular, we present tips for writing an excellent statistical analysis plan or biostatistical core for a biomedical or public health research grant with a primary focus outside of biostatistics. We will focus our attention on R01 research project grants and multi-project awards (e.g., P01, P30, P50, U19).

Multi-project awards support a multidisciplinary research team or group of investigators that focuses on a common research topic. They generally fund shared resources and facilities across multiple smaller research projects, and a biostatistics, data management, and/or bioinformatics core facility is often part of these proposals.

In an R01 proposal that does not involve statistics as a primary focus, the statistical portions of the grant usually contribute to the scores under the categories “Investigators,” “Approach,” and “Overall.” In the investigator category, reviewers are looking for evidence that the statistician or statistical analysis team has the skill and experience to evaluate the hypotheses in the specific aims. Your relevant skills and experience are judged based primarily on the information you provide in your biosketch(es) and the quality of the study design and analysis plan in the grant.

If you are a new researcher with relatively few publications, you should consider engaging a more senior biostatistician as a consultant or investigator on the grant to ensure the reviewers are comfortable with the level of statistical support. Reviewers will express their comfort with the planned study design and statistical analysis in the approach section of the grant, and both your credentials and statistical analysis plan/study design may affect the grant’s overall score.

For multi-project awards, a biostatistics, data management, and/or bioinformatics core facility is often scored as either acceptable or unacceptable, rather than using the typical 1–9 scale described in last month’s article. Unacceptable scores are not rare, so this scoring scheme does not mean the statistical section is less important than in other proposals.

Tips for Meeting Scientific Goals

Match the specific aims of the grant to your statistical analysis plan. Every hypothesis laid out in the specific aims should have a corresponding section in the analysis plan clearly describing how the hypothesis will be tested or otherwise evaluated. It is critical that the analysis plan is specific about how the investigator’s aims will be translated into hypotheses that you will then evaluate. It will be helpful if you use the same numbering system in the analysis plan that is used for the specific aims.

Know your audience. It is important to learn about the NIH review group that will score your application. Expectations for a statistical analysis section or biostatistics core may vary greatly across fields. Suppose the grant examines interactions between individuals’ genetic profiles and their diet in predicting cancer. Your grant may be reviewed by epidemiologists, bench scientists, or clinicians, and each type of reviewer would have different expectations of an excellent analysis plan. Current and previous review group rosters can be found at http://era.nih.gov/roster and can provide valuable information about the expertise (and expectations) of the review group. Previous grant reviews from the same review group can help you learn more about the review group’s expectations, even if they are from different proposals.

Provide something for everyone, explaining statistical concepts in clear, concise language that is accessible to nonstatisticians as well as to statisticians. As Taylor mentioned in last month’s issue, it is critical to “keep in mind the goal of making the application as easy as possible for reviewers to understand and appreciate.” Maybe you do really need that complex structural equations model or new methodology for dynamic treatment regimes to evaluate the specific aims; if so, it needs to be in the grant. However, in a nonstatistical review group, you may get three grant reviewers who have relatively little statistical knowledge. The reviewers may criticize an analysis plan if it comes across as overly involved or too ambitious. Be sure to take a little space or add a figure to explain the basic ideas of any complicated methods so a reviewer with a minimal background in statistics will get the big picture and understand why something more than a t -test is required.

Be specific. Don’t use boilerplate or a standard template for every grant you write. Reviewers will be looking to see how your analysis plan addresses the specific aims of the proposal. Have you addressed pertinent issues in the study at hand (e.g., a particular missing data problem, measurement error, or potential biases)? In a multi-project grant, reviewers will look to see whether the biostatistics core has the specific expertise to achieve all aims in the component grants. In some multi-project grants, you will need to show broad statistical expertise across biostatistics core members, as many multi-project grants devote considerable resources to helping new researchers get new projects off the ground.

Trust your collaborators. If they have a concern about the analysis plan, it is likely to be shared by the reviewers. Incorporating their feedback to improve the analysis plan will generally lead to a superior final product. But not always. Stick to your guns if you really think your collaborators are going in the wrong direction (e.g., using medical students for data cleaning is not acceptable, even if this has worked well for them in the past).

A second pair of eyes is often helpful. Offer to look over a colleague’s grants in exchange for having your colleague review yours.

Data cleaning and reproducibility are two critical concerns. Be sure you have addressed these issues in your proposal and have budgeted appropriately.

Keep your eyes open for methodological opportunities. Many statisticians are successful at getting their own grants (as PI) based on interesting methodological issues that arise in collaboration.

Operational Aspects Critical to Meeting Scientific Goals

Set expectations early so there are no unpleasant surprises at the time of submission. Will you be a co-investigator (this is standard) or dual PI (uncommon but appropriate if there is a large statistical component)? Often, the roles “biostatistician” or “statistician” are used, and these generally indicate more basic support, rather than doctoral-level scientific leadership, with a few notable exceptions (one that comes to mind is the biostatistics core of a multi-project grant, in which multiple researchers may be listed with minimal support just in case their expertise is needed). What percent effort will be required of the statistical team? Do you need graduate student support and computing resources? Who will be responsible for data entry, data management, and archiving code? What is the time frame for grant writing?

Be realistic. Don’t promise too much work for too little time. Nobody is happy if you cannot meet the goals you set. When the analysis is extensive or involves some new methodological territory, be sure your percent effort is substantial. For many projects, 1.5 months of effort plus a graduate student research assistant will be appropriate in analysis years, with adjustment of the effort required if early years of the grant do not involve any data analysis (however, you would generally still want around 0.6–1.0 months of funding yourself if you expect to provide input on the study design and other important issues that may arise early in the study).

Along these lines, be aware that sometimes grants will face cuts, either by the PI right before submission (to get the budget within pre-specified limits) or by NIH at the time of funding, and the PI generally has wide latitude in how to apply the cuts. You should not be afraid to put your foot down if your 10% effort plus a graduate student is cut to only 4% of your own time with no graduate student. In this case, you would explain how much of your time is available on that limited basis (e.g., 4% may be only enough to support your participation in a single 1.5 hour meeting per week, with no statistical analysis included, and, in that case, you may prefer to spend your time on projects that will provide you with more interesting work) and negotiate to obtain enough effort to support the work needed. Your department chair (or a senior faculty member, if you are a junior faculty member) can be helpful in such negotiations. Don’t be afraid to refuse to work on a project if the % effort is truly inadequate (though you should check with colleagues to be sure your version of inadequate is not out of line).

Read the review criteria before writing your sections of the grant. For some grants, the review criteria specifically address statistical analysis plans. Responsiveness to these criteria can greatly enhance your chances of success in the peer review process.

Cores in multi-project awards can be tricky to write. Sometimes, a reviewer may be assigned to review only your core, and sometimes a reviewer may review the entire grant. Thus, the core should be responsive to the research projects in the grant while also standing alone for review. Biostatistics cores have special requirements beyond statistical analysis plans of R01s. A core needs a specific leader who will be responsible for all core activities. The application must explain the organization of the core and clearly describe how it operates, including how researcher requests to use the core will be prioritized. Core services will vary based on the goals of the multi-project award but typically provide expertise for the planning, conduct, analysis, and reporting of studies; scientific computing; data management; manuscript preparation; and training of core users (reviewers often look favorably on cores that incorporate a training component by providing relevant workshops and seminars). Often, a strong case can be made to include time for methodological research by core biostatisticians when the multi-project aims would benefit from enhanced statistical methodology. It is always a good idea to provide specific names for all personnel (including programmers and graduate students), rather than budgeting for unnamed individuals in these applications.

Be committed. Carefully tailor the personal statement on your biosketch and the accompanying list of publications to the grant application at hand. For example, you will want to include papers that are co-authored with your collaborators on the current application and other publications that show you have already worked in areas relevant to the grant. If the grant requires statistical assistance in an area in which you have no expertise, you may want to bring another statistician onto the team as co-investigator or a consultant to the grant. If you do not show you have the skills to carry out the proposed analysis, or if you do not look fully engaged with the grant, the grant may get less favorable scores for the investigators, approach, and overall components.

Block off time for last-minute changes well in advance. Your colleagues may have others inside the university review the grant before submission, and an aim may be replaced at the last minute. This could require a new analysis plan, new power calculations, etc. While major last-minute changes should not be a regular occurrence, this happens periodically, even with outstanding collaborators, and you should not be surprised to have requests for 11th-hour edits.

Meetings such as ENAR and JSM often offer roundtable discussions on writing statistical components of non-statistical grants. These discussions are a great way to share good (and bad!) experiences with colleagues to increase the probability of success in the future. Good luck!

Comments are closed.

Amstat News is the monthly membership magazine of the American Statistical Association, bringing you news and notices of the ASA, its chapters, its sections, and its members. Other departments in the magazine include announcements and news of upcoming meetings, continuing education courses, and statistics awards.

• The American Statistical Association
• Calendar of Events
• Awards and Recognition

Departments

Advertisers.

PROFESSIONAL OPPORTUNITIES FDA US Census Bureau

“ Let’s tell our stories, so others will know the value of calling on professional statisticians and data scientists to drive discovery and inform decisions.”

— Bonnie Ghosh-Dastidar, ASA President

Editorial Staff

Managing Editor Megan Murphy

Graphic Designers / Production Coordinators Olivia Brown Meg Ruyle

Communications Strategist Val Nirala

Advertising Manager Christina Bonner

Contributing Staff Members Kim Gilliam

Amstat News American Statistical Association 732 North Washington Street Alexandria, VA 22314-1904 (703) 684-1221 www.amstat.org Address Changes Amstat News Advertising

• Privacy Policy

Home » Research Proposal – Types, Template and Example

Research Proposal – Types, Template and Example

Table of Contents

Research Proposal

Research proposal is a document that outlines a proposed research project . It is typically written by researchers, scholars, or students who intend to conduct research to address a specific research question or problem.

Types of Research Proposal

Research proposals can vary depending on the nature of the research project and the specific requirements of the funding agency, academic institution, or research program. Here are some common types of research proposals:

Academic Research Proposal

This is the most common type of research proposal, which is prepared by students, scholars, or researchers to seek approval and funding for an academic research project. It includes all the essential components mentioned earlier, such as the introduction, literature review , methodology , and expected outcomes.

Grant Proposal

A grant proposal is specifically designed to secure funding from external sources, such as government agencies, foundations, or private organizations. It typically includes additional sections, such as a detailed budget, project timeline, evaluation plan, and a description of the project’s alignment with the funding agency’s priorities and objectives.

Dissertation or Thesis Proposal

Students pursuing a master’s or doctoral degree often need to submit a proposal outlining their intended research for their dissertation or thesis. These proposals are usually more extensive and comprehensive, including an in-depth literature review, theoretical framework, research questions or hypotheses, and a detailed methodology.

Research Project Proposal

This type of proposal is often prepared by researchers or research teams within an organization or institution. It outlines a specific research project that aims to address a particular problem, explore a specific area of interest, or provide insights for decision-making. Research project proposals may include sections on project management, collaboration, and dissemination of results.

Research Fellowship Proposal

Researchers or scholars applying for research fellowships may be required to submit a proposal outlining their proposed research project. These proposals often emphasize the novelty and significance of the research and its alignment with the goals and objectives of the fellowship program.

Collaborative Research Proposal

In cases where researchers from multiple institutions or disciplines collaborate on a research project, a collaborative research proposal is prepared. This proposal highlights the objectives, responsibilities, and contributions of each collaborator, as well as the overall research plan and coordination mechanisms.

Research Proposal Outline

A research proposal typically follows a standard outline that helps structure the document and ensure all essential components are included. While the specific headings and subheadings may vary slightly depending on the requirements of your institution or funding agency, the following outline provides a general structure for a research proposal:

• Title of the research proposal
• Name of the researcher(s) or principal investigator(s)
• Affiliation or institution
• Date of submission
• A concise summary of the research proposal, typically limited to 200-300 words.
• Briefly introduce the research problem or question, state the objectives, summarize the methodology, and highlight the expected outcomes or significance of the research.
• Provide an overview of the subject area and the specific research problem or question.
• Present relevant background information, theories, or concepts to establish the need for the research.
• Clearly state the research objectives or research questions that the study aims to address.
• Indicate the significance or potential contributions of the research.
• Summarize and analyze relevant studies, theories, or scholarly works.
• Identify research gaps or unresolved issues that your study intends to address.
• Highlight the novelty or uniqueness of your research.
• Describe the overall approach or research design that will be used (e.g., experimental, qualitative, quantitative).
• Justify the chosen approach based on the research objectives and question.
• Explain how data will be collected (e.g., surveys, interviews, experiments).
• Describe the sampling strategy and sample size, if applicable.
• Address any ethical considerations related to data collection.
• Outline the data analysis techniques or statistical methods that will be applied.
• Explain how the data will be interpreted and analyzed to answer the research question(s).
• Provide a detailed schedule or timeline that outlines the various stages of the research project.
• Specify the estimated duration for each stage, including data collection, analysis, and report writing.
• State the potential outcomes or results of the research.
• Discuss the potential significance or contributions of the study to the field.
• Address any potential limitations or challenges that may be encountered.
• Identify the resources required to conduct the research, such as funding, equipment, or access to data.
• Specify any collaborations or partnerships necessary for the successful completion of the study.
• Include a list of cited references in the appropriate citation style (e.g., APA, MLA).

———————————————————————————————–

Research Proposal Example Template

Here’s an example of a research proposal to give you an idea of how it can be structured:

Title: The Impact of Social Media on Adolescent Well-being: A Mixed-Methods Study

This research proposal aims to investigate the impact of social media on the well-being of adolescents. The study will employ a mixed-methods approach, combining quantitative surveys and qualitative interviews to gather comprehensive data. The research objectives include examining the relationship between social media use and mental health, exploring the role of peer influence in shaping online behaviors, and identifying strategies for promoting healthy social media use among adolescents. The findings of this study will contribute to the understanding of the effects of social media on adolescent well-being and inform the development of targeted interventions.

1. Introduction

1.1 Background and Context:

Adolescents today are immersed in social media platforms, which have become integral to their daily lives. However, concerns have been raised about the potential negative impact of social media on their well-being, including increased rates of depression, anxiety, and body dissatisfaction. It is crucial to investigate this phenomenon further and understand the underlying mechanisms to develop effective strategies for promoting healthy social media use among adolescents.

1.2 Research Objectives:

The main objectives of this study are:

• To examine the association between social media use and mental health outcomes among adolescents.
• To explore the influence of peer relationships and social comparison on online behaviors.
• To identify strategies and interventions to foster positive social media use and enhance adolescent well-being.

2. Literature Review

Extensive research has been conducted on the impact of social media on adolescents. Existing literature suggests that excessive social media use can contribute to negative outcomes, such as low self-esteem, cyberbullying, and addictive behaviors. However, some studies have also highlighted the positive aspects of social media, such as providing opportunities for self-expression and social support. This study will build upon this literature by incorporating both quantitative and qualitative approaches to gain a more nuanced understanding of the relationship between social media and adolescent well-being.

3. Methodology

3.1 Research Design:

This study will adopt a mixed-methods approach, combining quantitative surveys and qualitative interviews. The quantitative phase will involve administering standardized questionnaires to a representative sample of adolescents to assess their social media use, mental health indicators, and perceived social support. The qualitative phase will include in-depth interviews with a subset of participants to explore their experiences, motivations, and perceptions related to social media use.

3.2 Data Collection Methods:

Quantitative data will be collected through an online survey distributed to schools in the target region. The survey will include validated scales to measure social media use, mental health outcomes, and perceived social support. Qualitative data will be collected through semi-structured interviews with a purposive sample of participants. The interviews will be audio-recorded and transcribed for thematic analysis.

3.3 Data Analysis:

Quantitative data will be analyzed using descriptive statistics and regression analysis to examine the relationships between variables. Qualitative data will be analyzed thematically to identify common themes and patterns within participants’ narratives. Integration of quantitative and qualitative findings will provide a comprehensive understanding of the research questions.

4. Timeline

The research project will be conducted over a period of 12 months, divided into specific phases, including literature review, study design, data collection, analysis, and report writing. A detailed timeline outlining the key milestones and activities is provided in Appendix A.

5. Expected Outcomes and Significance

This study aims to contribute to the existing literature on the impact of social media on adolescent well-being by employing a mixed-methods approach. The findings will inform the development of evidence-based interventions and guidelines to promote healthy social media use among adolescents. This research has the potential to benefit adolescents, parents, educators, and policymakers by providing insights into the complex relationship between social media and well-being and offering strategies for fostering positive online experiences.

6. Resources

The resources required for this research include access to a representative sample of adolescents, research assistants for data collection, statistical software for data analysis, and funding to cover survey administration and participant incentives. Ethical considerations will be taken into account, ensuring participant confidentiality and obtaining informed consent.

7. References

Research Proposal Writing Guide

Writing a research proposal can be a complex task, but with proper guidance and organization, you can create a compelling and well-structured proposal. Here’s a step-by-step guide to help you through the process:

• Understand the requirements: Familiarize yourself with the guidelines and requirements provided by your institution, funding agency, or program. Pay attention to formatting, page limits, specific sections or headings, and any other instructions.
• Identify your research topic: Choose a research topic that aligns with your interests, expertise, and the goals of your program or funding opportunity. Ensure that your topic is specific, focused, and relevant to the field of study.
• Conduct a literature review : Review existing literature and research relevant to your topic. Identify key theories, concepts, methodologies, and findings related to your research question. This will help you establish the context, identify research gaps, and demonstrate the significance of your proposed study.
• Define your research objectives and research question(s): Clearly state the objectives you aim to achieve with your research. Formulate research questions that address the gaps identified in the literature review. Your research objectives and questions should be specific, measurable, achievable, relevant, and time-bound (SMART).
• Develop a research methodology: Determine the most appropriate research design and methodology for your study. Consider whether quantitative, qualitative, or mixed-methods approaches will best address your research question(s). Describe the data collection methods, sampling strategy, data analysis techniques, and any ethical considerations associated with your research.
• Create a research plan and timeline: Outline the various stages of your research project, including tasks, milestones, and deadlines. Develop a realistic timeline that considers factors such as data collection, analysis, and report writing. This plan will help you stay organized and manage your time effectively throughout the research process.
• A. Introduction: Provide background information on the research problem, highlight its significance, and introduce your research objectives and questions.
• B. Literature review: Summarize relevant literature, identify gaps, and justify the need for your proposed research.
• C . Methodology: Describe your research design, data collection methods, sampling strategy, data analysis techniques, and any ethical considerations.
• D . Expected outcomes and significance: Explain the potential outcomes, contributions, and implications of your research.
• E. Resources: Identify the resources required to conduct your research, such as funding, equipment, or access to data.
• F . References: Include a list of cited references in the appropriate citation style.
• Revise and proofread: Review your proposal for clarity, coherence, and logical flow. Check for grammar and spelling errors. Seek feedback from mentors, colleagues, or advisors to refine and improve your proposal.
• Finalize and submit: Make any necessary revisions based on feedback and finalize your research proposal. Ensure that you have met all the requirements and formatting guidelines. Submit your proposal within the specified deadline.

Research Proposal Length

The length of a research proposal can vary depending on the specific guidelines provided by your institution or funding agency. However, research proposals typically range from 1,500 to 3,000 words, excluding references and any additional supporting documents.

Purpose of Research Proposal

The purpose of a research proposal is to outline and communicate your research project to others, such as academic institutions, funding agencies, or potential collaborators. It serves several important purposes:

• Demonstrate the significance of the research: A research proposal explains the importance and relevance of your research project. It outlines the research problem or question, highlights the gaps in existing knowledge, and explains how your study will contribute to the field. By clearly articulating the significance of your research, you can convince others of its value and potential impact.
• Provide a clear research plan: A research proposal outlines the methodology, design, and approach you will use to conduct your study. It describes the research objectives, data collection methods, data analysis techniques, and potential outcomes. By presenting a clear research plan, you demonstrate that your study is well-thought-out, feasible, and likely to produce meaningful results.
• Secure funding or support: For researchers seeking funding or support for their projects, a research proposal is essential. It allows you to make a persuasive case for why your research is deserving of financial resources or institutional backing. The proposal explains the budgetary requirements, resources needed, and potential benefits of the research, helping you secure the necessary funding or support.
• Seek feedback and guidance: Presenting a research proposal provides an opportunity to receive feedback and guidance from experts in your field. It allows you to engage in discussions and receive suggestions for refining your research plan, improving the methodology, or addressing any potential limitations. This feedback can enhance the quality of your study and increase its chances of success.
• Establish ethical considerations: A research proposal also addresses ethical considerations associated with your study. It outlines how you will ensure participant confidentiality, obtain informed consent, and adhere to ethical guidelines and regulations. By demonstrating your awareness and commitment to ethical research practices, you build trust and credibility in your proposed study.

Importance of Research Proposal

The research proposal holds significant importance in the research process. Here are some key reasons why research proposals are important:

• Planning and organization: A research proposal requires careful planning and organization of your research project. It forces you to think through the research objectives, research questions, methodology, and potential outcomes before embarking on the actual study. This planning phase helps you establish a clear direction and framework for your research, ensuring that your efforts are focused and purposeful.
• Demonstrating the significance of the research: A research proposal allows you to articulate the significance and relevance of your study. By providing a thorough literature review and clearly defining the research problem or question, you can showcase the gaps in existing knowledge that your research aims to address. This demonstrates to others, such as funding agencies or academic institutions, why your research is important and deserving of support.
• Obtaining funding and resources: Research proposals are often required to secure funding for your research project. Funding agencies and organizations need to evaluate the feasibility and potential impact of the proposed research before allocating resources. A well-crafted research proposal helps convince funders of the value of your research and increases the likelihood of securing financial support, grants, or scholarships.
• Receiving feedback and guidance: Presenting a research proposal provides an opportunity to seek feedback and guidance from experts in your field. By sharing your research plan and objectives with others, you can benefit from their insights and suggestions. This feedback can help refine your research design, strengthen your methodology, and ensure that your study is rigorous and well-informed.
• Ethical considerations: A research proposal addresses ethical considerations associated with your study. It outlines how you will protect the rights and welfare of participants, maintain confidentiality, obtain informed consent, and adhere to ethical guidelines and regulations. This emphasis on ethical practices ensures that your research is conducted responsibly and with integrity.
• Enhancing collaboration and partnerships: A research proposal can facilitate collaborations and partnerships with other researchers, institutions, or organizations. When presenting your research plan, you may attract the interest of potential collaborators who share similar research interests or possess complementary expertise. Collaborative partnerships can enrich your study, expand your resources, and foster knowledge exchange.
• Establishing a research trajectory: A research proposal serves as a foundation for your research project. Once approved, it becomes a roadmap that guides your study’s implementation, data collection, analysis, and reporting. It helps maintain focus and ensures that your research stays on track and aligned with the initial objectives.

When to Write Research Proposal

The timing of when to write a research proposal can vary depending on the specific requirements and circumstances. However, here are a few common situations when it is appropriate to write a research proposal:

• Academic research: If you are a student pursuing a research degree, such as a Ph.D. or Master’s by research, you will typically be required to write a research proposal as part of the application process. This is usually done before starting the research program to outline your proposed study and seek approval from the academic institution.
• Funding applications: When applying for research grants, scholarships, or funding from organizations or institutions, you will often need to submit a research proposal. Funding agencies require a detailed description of your research project, including its objectives, methodology, and expected outcomes. Writing a research proposal in this context is necessary to secure financial support for your study.
• Research collaborations: When collaborating with other researchers, institutions, or organizations on a research project, it is common to prepare a research proposal. This helps outline the research objectives, roles and responsibilities, and expected contributions from each party. Writing a research proposal in this case allows all collaborators to align their efforts and ensure a shared understanding of the project.
• Research project within an organization: If you are conducting research within an organization, such as a company or government agency, you may be required to write a research proposal to gain approval and support for your study. This proposal outlines the research objectives, methodology, resources needed, and expected outcomes, ensuring that the project aligns with the organization’s goals and objectives.
• Independent research projects: Even if you are not required to write a research proposal, it can still be beneficial to develop one for your independent research projects. Writing a research proposal helps you plan and structure your study, clarify your research objectives, and anticipate potential challenges or limitations. It also allows you to communicate your research plans effectively to supervisors, mentors, or collaborators.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Business Proposal – Templates, Examples and Guide

Proposal – Types, Examples, and Writing Guide

Grant Proposal – Example, Template and Guide

How To Write A Proposal – Step By Step Guide...

How To Write A Grant Proposal – Step-by-Step...

How To Write A Business Proposal – Step-by-Step...

Research Proposal Example/Sample

Detailed Walkthrough + Free Proposal Template

If you’re getting started crafting your research proposal and are looking for a few examples of research proposals , you’ve come to the right place.

In this video, we walk you through two successful (approved) research proposals , one for a Master’s-level project, and one for a PhD-level dissertation. We also start off by unpacking our free research proposal template and discussing the four core sections of a research proposal, so that you have a clear understanding of the basics before diving into the actual proposals.

• Research proposal example/sample – Master’s-level (PDF/Word)
• Research proposal example/sample – PhD-level (PDF/Word)
• Proposal template (Fully editable) 

If you’re working on a research proposal for a dissertation or thesis, you may also find the following useful:

• Research Proposal Bootcamp : Learn how to write a research proposal as efficiently and effectively as possible
• 1:1 Proposal Coaching : Get hands-on help with your research proposal

PS – If you’re working on a dissertation, be sure to also check out our collection of dissertation and thesis examples here .

FAQ: Research Proposal Example

Research proposal example: frequently asked questions, are the sample proposals real.

Yes. The proposals are real and were approved by the respective universities.

Can I copy one of these proposals for my own research?

As we discuss in the video, every research proposal will be slightly different, depending on the university’s unique requirements, as well as the nature of the research itself. Therefore, you’ll need to tailor your research proposal to suit your specific context.

You can learn more about the basics of writing a research proposal here .

How do I get the research proposal template?

You can access our free proposal template here .

Is the proposal template really free?

Yes. There is no cost for the proposal template and you are free to use it as a foundation for your research proposal.

Where can I learn more about proposal writing?

For self-directed learners, our Research Proposal Bootcamp is a great starting point.

For students that want hands-on guidance, our private coaching service is recommended.

Psst… there’s more!

This post is an extract from our bestselling short course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

You Might Also Like:

10 Comments

I am at the stage of writing my thesis proposal for a PhD in Management at Altantic International University. I checked on the coaching services, but it indicates that it’s not available in my area. I am in South Sudan. My proposed topic is: “Leadership Behavior in Local Government Governance Ecosystem and Service Delivery Effectiveness in Post Conflict Districts of Northern Uganda”. I will appreciate your guidance and support

GRADCOCH is very grateful motivated and helpful for all students etc. it is very accorporated and provide easy access way strongly agree from GRADCOCH.

Proposal research departemet management

I am at the stage of writing my thesis proposal for a masters in Analysis of w heat commercialisation by small holders householdrs at Hawassa International University. I will appreciate your guidance and support

please provide a attractive proposal about foreign universities .It would be your highness.

comparative constitutional law

Kindly guide me through writing a good proposal on the thesis topic; Impact of Artificial Intelligence on Financial Inclusion in Nigeria. Thank you

Kindly help me write a research proposal on the topic of impacts of artisanal gold panning on the environment

I am in the process of research proposal for my Master of Art with a topic : “factors influence on first-year students’s academic adjustment”. I am absorbing in GRADCOACH and interested in such proposal sample. However, it is great for me to learn and seeking for more new updated proposal framework from GRADCAOCH.

Submit a Comment Cancel reply

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

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

• Print Friendly

Top 99+ Trending Statistics Research Topics for Students

Being a statistics student, finding the best statistics research topics is quite challenging. But not anymore; find the best statistics research topics now!!!

Statistics is one of the tough subjects because it consists of lots of formulas, equations and many more. Therefore the students need to spend their time to understand these concepts. And when it comes to finding the best statistics research project for their topics, statistics students are always looking for someone to help them. 

In this blog, we will share with you the most interesting and trending statistics research topics in 2023. It will not just help you to stand out in your class but also help you to explore more about the world.

If you face any problem regarding statistics, then don’t worry. You can get the best statistics assignment help from one of our experts.

As you know, it is always suggested that you should work on interesting topics. That is why we have mentioned the most interesting research topics for college students and high school students. Here in this blog post, we will share with you the list of 99+ awesome statistics research topics.

Why Do We Need to Have Good Statistics Research Topics?

Table of Contents

Having a good research topic will not just help you score good grades, but it will also allow you to finish your project quickly. Because whenever we work on something interesting, our productivity automatically boosts. Thus, you need not invest lots of time and effort, and you can achieve the best with minimal effort and time. 

What Are Some Interesting Research Topics?

If we talk about the interesting research topics in statistics, it can vary from student to student. But here are the key topics that are quite interesting for almost every student:-

• Literacy rate in a city.
• Abortion and pregnancy rate in the USA.
• Eating disorders in the citizens.
• Parent role in self-esteem and confidence of the student.
• Uses of AI in our daily life to business corporates.

Top 99+ Trending Statistics Research Topics For 2023

Here in this section, we will tell you more than 99 trending statistics research topics:

Sports Statistics Research Topics

• Statistical analysis for legs and head injuries in Football.
• Statistical analysis for shoulder and knee injuries in MotoGP.
• Deep statistical evaluation for the doping test in sports from the past decade.
• Statistical observation on the performance of athletes in the last Olympics.
• Role and effect of sports in the life of the student.

Psychology Research Topics for Statistics

• Deep statistical analysis of the effect of obesity on the student’s mental health in high school and college students.
• Statistical evolution to find out the suicide reason among students and adults.
• Statistics analysis to find out the effect of divorce on children in a country.
• Psychology affects women because of the gender gap in specific country areas.
• Statistics analysis to find out the cause of online bullying in students’ lives. 
• In Psychology, PTSD and descriptive tendencies are discussed.
• The function of researchers in statistical testing and probability.
• Acceptable significance and probability thresholds in clinical Psychology.
• The utilization of hypothesis and the role of P 0.05 for improved comprehension.
• What types of statistical data are typically rejected in psychology?
• The application of basic statistical principles and reasoning in psychological analysis.
• The role of correlation is when several psychological concepts are at risk.
• Actual case study learning and modeling are used to generate statistical reports.
• In psychology, naturalistic observation is used as a research sample.
• How should descriptive statistics be used to represent behavioral data sets?

Applied Statistics Research Topics

• Does education have a deep impact on the financial success of an individual?
• The investment in digital technology is having a meaningful return for corporations?
• The gap of financial wealth between rich and poor in the USA.
• A statistical approach to identify the effects of high-frequency trading in financial markets.
• Statistics analysis to determine the impact of the multi-agent model in financial markets. 

Personalized Medicine Statistics Research Topics

• Statistical analysis on the effect of methamphetamine on substance abusers.
• Deep research on the impact of the Corona vaccine on the Omnicrone variant. 
• Find out the best cancer treatment approach between orthodox therapies and alternative therapies.
• Statistics analysis to identify the role of genes in the child’s overall immunity.
• What factors help the patients to survive from Coronavirus .

Experimental Design Statistics Research Topics

• Generic vs private education is one of the best for the students and has better financial return.
• Psychology vs physiology: which leads the person not to quit their addictions?
• Effect of breastmilk vs packed milk on the infant child overall development
• Which causes more accidents: male alcoholics vs female alcoholics.
• What causes the student not to reveal the cyberbullying in front of their parents in most cases. 

Easy Statistics Research Topics

• Application of statistics in the world of data science
• Statistics for finance: how statistics is helping the company to grow their finance
• Advantages and disadvantages of Radar chart
• Minor marriages in south-east Asia and African countries.
• Discussion of ANOVA and correlation.
• What statistical methods are most effective for active sports?
• When measuring the correctness of college tests, a ranking statistical approach is used.
• Statistics play an important role in Data Mining operations.
• The practical application of heat estimation in engineering fields.
• In the field of speech recognition, statistical analysis is used.
• Estimating probiotics: how much time is necessary for an accurate statistical sample?
• How will the United States population grow in the next twenty years?
• The legislation and statistical reports deal with contentious issues.
• The application of empirical entropy approaches with online grammar checking.
• Transparency in statistical methodology and the reporting system of the United States Census Bureau.

Statistical Research Topics for High School

• Uses of statistics in chemometrics
• Statistics in business analytics and business intelligence
• Importance of statistics in physics.
• Deep discussion about multivariate statistics
• Uses of Statistics in machine learning

Survey Topics for Statistics

• Gather the data of the most qualified professionals in a specific area.
• Survey the time wasted by the students in watching Tvs or Netflix.
• Have a survey the fully vaccinated people in the USA 
• Gather information on the effect of a government survey on the life of citizens
• Survey to identify the English speakers in the world.

Statistics Research Paper Topics for Graduates

• Have a deep decision of Bayes theorems
• Discuss the Bayesian hierarchical models
• Analysis of the process of Japanese restaurants. 
• Deep analysis of Lévy’s continuity theorem
• Analysis of the principle of maximum entropy

AP Statistics Topics

• Discuss about the importance of econometrics
• Analyze the pros and cons of Probit Model
• Types of probability models and their uses
• Deep discussion of ortho stochastic matrix
• Find out the ways to get an adjacency matrix quickly

Good Statistics Research Topics 

• National income and the regulation of cryptocurrency.
• The benefits and drawbacks of regression analysis.
• How can estimate methods be used to correct statistical differences?
• Mathematical prediction models vs observation tactics.
• In sociology research, there is bias in quantitative data analysis.
• Inferential analytical approaches vs. descriptive statistics.
• How reliable are AI-based methods in statistical analysis?
• The internet news reporting and the fluctuations: statistics reports.
• The importance of estimate in modeled statistics and artificial sampling.

Business Statistics Topics

• Role of statistics in business in 2023
• Importance of business statistics and analytics
• What is the role of central tendency and dispersion in statistics
• Best process of sampling business data.
• Importance of statistics in big data.
• The characteristics of business data sampling: benefits and cons of software solutions.
• How may two different business tasks be tackled concurrently using linear regression analysis?
• In economic data relations, index numbers, random probability, and correctness are all important.
• The advantages of a dataset approach to statistics in programming statistics.
• Commercial statistics: how should the data be prepared for maximum accuracy?

Statistical Research Topics for College Students

• Evaluate the role of John Tukey’s contribution to statistics.
• The role of statistics to improve ADHD treatment.
• The uses and timeline of probability in statistics.
• Deep analysis of Gertrude Cox’s experimental design in statistics.
• Discuss about Florence Nightingale in statistics.
• What sorts of music do college students prefer?
• The Main Effect of Different Subjects on Student Performance.
• The Importance of Analytics in Statistics Research.
• The Influence of a Better Student in Class.
• Do extracurricular activities help in the transformation of personalities?
• Backbenchers’ Impact on Class Performance.
• Medication’s Importance in Class Performance.
• Are e-books better than traditional books?
• Choosing aspects of a subject in college

How To Write Good Statistics Research Topics?

So, the main question that arises here is how you can write good statistics research topics. The trick is understanding the methodology that is used to collect and interpret statistical data. However, if you are trying to pick any topic for your statistics project, you must think about it before going any further. 

As a result, it will teach you about the data types that will be researched because the sample will be chosen correctly. On the other hand, your basic outline for choosing the correct topics is as follows:

• Introduction of a problem
• Methodology explanation and choice. 
• Statistical research itself is in the main part (Body Part). 
• Samples deviations and variables. 
• Lastly, statistical interpretation is your last part (conclusion). 

Note:   Always include the sources from which you obtained the statistics data.

Top 3 Tips to Choose Good Statistics Research Topics

It can be quite easy for some students to pick a good statistics research topic without the help of an essay writer. But we know that it is not a common scenario for every student. That is why we will mention some of the best tips that will help you choose good statistics research topics for your next project. Either you are in a hurry or have enough time to explore. These tips will help you in every scenario.

1. Narrow down your research topic

We all start with many topics as we are not sure about our specific interests or niche. The initial step to picking up a good research topic for college or school students is to narrow down the research topic.

For this, you need to categorize the matter first. And then pick a specific category as per your interest. After that, brainstorm about the topic’s content and how you can make the points catchy, focused, directional, clear, and specific. 

2. Choose a topic that gives you curiosity

After categorizing the statistics research topics, it is time to pick one from the category. Don’t pick the most common topic because it will not help your grades and knowledge. Instead of it, please choose the best one, in which you have little information, or you are more likely to explore it.

In a statistics research paper, you always can explore something beyond your studies. By doing this, you will be more energetic to work on this project. And you will also feel glad to get them lots of information you were willing to have but didn’t get because of any reasons.

It will also make your professor happy to see your work. Ultimately it will affect your grades with a positive attitude.

3. Choose a manageable topic

Now you have decided on the topic, but you need to make sure that your research topic should be manageable. You will have limited time and resources to complete your project if you pick one of the deep statistics research topics with massive information.

Then you will struggle at the last moment and most probably not going to finish your project on time. Therefore, spend enough time exploring the topic and have a good idea about the time duration and resources you will use for the project. 

Statistics research topics are massive in numbers. Because statistics operations can be performed on anything from our psychology to our fitness. Therefore there are lots more statistics research topics to explore. But if you are not finding it challenging, then you can take the help of our statistics experts . They will help you to pick the most interesting and trending statistics research topics for your projects. 

With this help, you can also save your precious time to invest it in something else. You can also come up with a plethora of topics of your choice and we will help you to pick the best one among them. Apart from that, if you are working on a project and you are not sure whether that is the topic that excites you to work on it or not. Then we can also help you to clear all your doubts on the statistics research topic. 

Frequently Asked Questions

Q1. what are some good topics for the statistics project.

Have a look at some good topics for statistics projects:- 1. Research the average height and physics of basketball players. 2. Birth and death rate in a specific city or country. 3. Study on the obesity rate of children and adults in the USA. 4. The growth rate of China in the past few years 5. Major causes of injury in Football

Q2. What are the topics in statistics?

Statistics has lots of topics. It is hard to cover all of them in a short answer. But here are the major ones: conditional probability, variance, random variable, probability distributions, common discrete, and many more. 

Q3. What are the top 10 research topics?

Here are the top 10 research topics that you can try in 2023:

1. Plant Science 2. Mental health 3. Nutritional Immunology 4. Mood disorders 5. Aging brains 6. Infectious disease 7. Music therapy 8. Political misinformation 9. Canine Connection 10. Sustainable agriculture

Related Posts

How to Find the Best Online Statistics Homework Help

Why SPSS Homework Help Is An Important aspect for Students?

• Research Process

Writing a Scientific Research Project Proposal

• 5 minute read
• 107.4K views

Table of Contents

The importance of a well-written research proposal cannot be underestimated. Your research really is only as good as your proposal. A poorly written, or poorly conceived research proposal will doom even an otherwise worthy project. On the other hand, a well-written, high-quality proposal will increase your chances for success.

In this article, we’ll outline the basics of writing an effective scientific research proposal, including the differences between research proposals, grants and cover letters. We’ll also touch on common mistakes made when submitting research proposals, as well as a simple example or template that you can follow.

What is a scientific research proposal?

The main purpose of a scientific research proposal is to convince your audience that your project is worthwhile, and that you have the expertise and wherewithal to complete it. The elements of an effective research proposal mirror those of the research process itself, which we’ll outline below. Essentially, the research proposal should include enough information for the reader to determine if your proposed study is worth pursuing.

It is not an uncommon misunderstanding to think that a research proposal and a cover letter are the same things. However, they are different. The main difference between a research proposal vs cover letter content is distinct. Whereas the research proposal summarizes the proposal for future research, the cover letter connects you to the research, and how you are the right person to complete the proposed research.

There is also sometimes confusion around a research proposal vs grant application. Whereas a research proposal is a statement of intent, related to answering a research question, a grant application is a specific request for funding to complete the research proposed. Of course, there are elements of overlap between the two documents; it’s the purpose of the document that defines one or the other.

Scientific Research Proposal Format

Although there is no one way to write a scientific research proposal, there are specific guidelines. A lot depends on which journal you’re submitting your research proposal to, so you may need to follow their scientific research proposal template.

In general, however, there are fairly universal sections to every scientific research proposal. These include:

• Title: Make sure the title of your proposal is descriptive and concise. Make it catch and informative at the same time, avoiding dry phrases like, “An investigation…” Your title should pique the interest of the reader.
• Abstract: This is a brief (300-500 words) summary that includes the research question, your rationale for the study, and any applicable hypothesis. You should also include a brief description of your methodology, including procedures, samples, instruments, etc.
• Introduction: The opening paragraph of your research proposal is, perhaps, the most important. Here you want to introduce the research problem in a creative way, and demonstrate your understanding of the need for the research. You want the reader to think that your proposed research is current, important and relevant.
• Background: Include a brief history of the topic and link it to a contemporary context to show its relevance for today. Identify key researchers and institutions also looking at the problem
• Literature Review: This is the section that may take the longest amount of time to assemble. Here you want to synthesize prior research, and place your proposed research into the larger picture of what’s been studied in the past. You want to show your reader that your work is original, and adds to the current knowledge.
• Research Design and Methodology: This section should be very clearly and logically written and organized. You are letting your reader know that you know what you are going to do, and how. The reader should feel confident that you have the skills and knowledge needed to get the project done.
• Preliminary Implications: Here you’ll be outlining how you anticipate your research will extend current knowledge in your field. You might also want to discuss how your findings will impact future research needs.
• Conclusion: This section reinforces the significance and importance of your proposed research, and summarizes the entire proposal.
• References/Citations: Of course, you need to include a full and accurate list of any and all sources you used to write your research proposal.

Common Mistakes in Writing a Scientific Research Project Proposal

Remember, the best research proposal can be rejected if it’s not well written or is ill-conceived. The most common mistakes made include:

• Not providing the proper context for your research question or the problem
• Failing to reference landmark/key studies
• Losing focus of the research question or problem
• Not accurately presenting contributions by other researchers and institutions
• Incompletely developing a persuasive argument for the research that is being proposed
• Misplaced attention on minor points and/or not enough detail on major issues
• Sloppy, low-quality writing without effective logic and flow
• Incorrect or lapses in references and citations, and/or references not in proper format
• The proposal is too long – or too short

Scientific Research Proposal Example

There are countless examples that you can find for successful research proposals. In addition, you can also find examples of unsuccessful research proposals. Search for successful research proposals in your field, and even for your target journal, to get a good idea on what specifically your audience may be looking for.

While there’s no one example that will show you everything you need to know, looking at a few will give you a good idea of what you need to include in your own research proposal. Talk, also, to colleagues in your field, especially if you are a student or a new researcher. We can often learn from the mistakes of others. The more prepared and knowledgeable you are prior to writing your research proposal, the more likely you are to succeed.

Language Editing Services

One of the top reasons scientific research proposals are rejected is due to poor logic and flow. Check out our Language Editing Services to ensure a great proposal , that’s clear and concise, and properly referenced. Check our video for more information, and get started today.

• Manuscript Review

Research Fraud: Falsification and Fabrication in Research Data

Research Team Structure

You may also like.

Descriptive Research Design and Its Myriad Uses

Five Common Mistakes to Avoid When Writing a Biomedical Research Paper

Making Technical Writing in Environmental Engineering Accessible

To Err is Not Human: The Dangers of AI-assisted Academic Writing

When Data Speak, Listen: Importance of Data Collection and Analysis Methods

Choosing the Right Research Methodology: A Guide for Researchers

Why is data validation important in research?

Writing a good review article

Input your search keywords and press Enter.

An official website of the United States government

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

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

• Publications
• Account settings

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

• Advanced Search
• Journal List
• HHS Author Manuscripts

Bridging Clinical Investigators and Statisticians: Writing the Statistical Methodology for a Research Proposal

Introduction.

Clinical research is judged to be valid not by the results but how it is designed and conducted. The cliché of ‘do it right or do it over’ is particularly apt in clinical research.

One of the questions a clinical investigator frequently asks in planning clinical research is “Do I need a statistician as part of my clinical research team?” The answer is “Yes!” since a statistician can help to optimize design, analysis and interpretation of results, and drawing conclusions. When developing a clinical research proposal, how early in the process should the clinical investigator contact the statistician? Answer - it is never too early. Statistics cannot rescue a poorly designed protocol after the study has begun. A statistician can be a valuable member of a clinical research team and often serves as a co-investigator. Large multicenter projects such as Phase III randomized clinical trials for drug approval by a regulatory agency nearly always have a statistician (or several) on their team. However, smaller, typically single center studies may also require rigorous statistical methodology in design and analysis. These studies are often devised by young clinical investigators launching their clinical research career who may have not collaborated with a statistician. Many clinical investigators are familiar with the statistical role in the analysis of research data 1 , but researchers may not be as aware of the role of a statistician in designing clinical research and developing the study protocol. In this paper we discuss topics and situations that clinical investigators and statisticians commonly encounter while planning a research study and writing the statistical methods section. We stress the importance of having the statistical methodology planned well in advance of conducting the clinical research study. Working in conjunction with a statistician can also be a key training opportunity for the clinical investigator beginning a clinical research career.

GETTING STARTED ON THE STATISTICAL ANALYSIS PLAN

Why work with a statistician.

The study design, sample size, and statistical analysis must be able to properly evaluate the research hypothesis set forth by the clinical investigator. Otherwise, the consequences of a poorly developed statistical approach may result in a failure to obtain extramural funding and result in a flawed clinical study that cannot adequately test the desired hypotheses. Statisticians provide design advice and develop the statistical methods that best correspond to the research hypothesis. For the planning of a clinical study, a statistician can provide valuable information on key design points as summarized in Table 1 . The statistician can discuss with the clinical investigators questions such as: Is the design valid? Overly ambitious? Will the data be analyzable?

The role of the statistician in developing the statistical plan

Very early in the planning stages, it is important to send the statistician a draft of the proposal. Any protocol changes may affect the required sample size and analysis plans so it is important to meet with the statistician throughout the planning stages and later if modifications have been made to the study design. Before the statistical section can be developed, what information does the statistician need? Questions from a statistician concerning design, power and sample size, and analysis may include:

• What is the research hypothesis?
• What is the type of study design?
• What is the most important measurement (primary outcome variable)?
• What is the type of variable and unit of measurement?
• What is a clinically meaningful difference for the primary outcome?
• How many subjects can be recruited or observed within a study period? How many groups or treatment arms are to be included in your design?
• Will there be an equal number of participants or observations in each group? i.e., what is the allocation ratio?
• How many total evaluations and measurements?
• For repeated measurements, what is the measurement interval?

You are not expected to have all the answers at your first meeting and ongoing conversations with the statistician can serve to develop these ideas. Eventually, the answers to these questions comprise the justification for the design selected, provide the basis for the sample size estimate, and drive the choice of statistical analysis. A brief consultation with a statistician will not be adequate to address these issues. The interaction with a statistician to construct the statistical section is not usually one meeting, email, or phone call. It is a process that will help you think through the design of your study. This is also an excellent opportunity to ask questions and enhance your statistical education. Additionally, the exchange of ideas is beneficial to the statistician who will better appreciate the clinical research question. The discussions with a statistician could lead to changes in study design, such as proposing a smaller, more focused study design to collect preliminary data.

A general outline of the statistical methods section is shown in Table 2 . There may be deviations from this format depending on the particular study design. The statistical write-up is rarely less than one page and may total several pages. Although some clinical investigators trained in statistics do prepare this section, more commonly the statistician constructs and writes up the statistical methods section for grants and protocols in close collaboration with the investigators. However, it is important that clinical investigators develop a conceptual understanding of the proposed statistical methodology. Take advantage of any study design and biostatistics classes offered at your institutions to make statistical collaborations more fruitful.

Outline of the statistical methods section

STUDY DESIGN

Type of design.

Before the statistical section can progress, the study design must be known. Study designs that are commonly used in clinical research include case-control, cohort, randomized controlled design, crossover, and factorial designs. A randomized controlled trial has many features but most commonly incorporates what is called a parallel group design where individuals are randomly assigned to a particular treatment or intervention group. In a crossover study, the subject participates in more than one study intervention phase, ideally studied in a random sequence, such as comparing triglyceride responses within the same individual on a low fat versus a high fat diet.

How do we select participants for the study? There are many types of sampling procedures, the basis of which is to avoid or reduce bias. Bias can be defined as ”a systematic tendency to produce an outcome that differs from the underlying truth”. 2 Although true randomness is the goal of a sampling, it is generally not achievable. The study subjects are not usually selected at random to participate in clinical research. Instead, in most clinical trials, the “random” element in randomization is that the consented subjects are assigned by chance to a particular treatment or intervention. The clinical inclusion and exclusion criteria coupled with informed consent will determine who will be the study participants and, ultimately, to what population the study results will be generalizable.

Sample size

With the study design and the make-up of the study sample determined, the sample size estimates can be obtained. Fundamental to estimating sample size are the concepts of statistical hypothesis testing, type I error, type II error, and power ( Table 3 ). In planning clinical research it is necessary to determine the number of subjects to be required so that the study achieves sufficient statistical power to detect the hypothesized effect. If the reader is not familiar with the concept of statistical hypothesis testing, introductory biostatistics texts and many web sites cover this topic. Briefly, in trials to demonstrate improved efficacy of a new treatment over placebo/standard treatments, the null hypothesis is that there is no difference between treatments and the alternative hypothesis is that there is a treatment difference. The research hypothesis usually corresponds to the alternative hypothesis which represents a minimal meaningful difference in clinical outcomes. Statistically, we either 1) reject the null hypothesis in favor of the alternative hypothesis or 2) we fail to reject the null hypothesis.

Definitions for statistical hypothesis testing

Typically, the sample size is computed to provide a fixed level of power under a specified alternative hypothesis. Power is an important consideration for several reasons. Low power can cause a true difference in clinical outcomes between study groups to go undetected. However, too much power may yield statistically significant results that are not meaningfully different to clinicians. The probability of Type I error (α) of 0.05 (two-sided) and power of 0.80 and 0.90 have been widely used for the sample size estimation in clinical trials. The sample size estimate will also allow the estimation of the total cost of the proposed study.

A clinical trial that is conducted without attention to sample size or power information takes the risks of either failing to detect clinically meaningful differences (Type II error) due to not enough subjects or taking an unnecessarily excessive number of samples for a study. Both cases fail to adhere to the Ethical Guidelines of the American Statistical Association which says “Avoid the use of excessive or inadequate number of research subjects by making informed recommendations for study size”. 3

What information is needed to calculate power and sample size?

The components that most sample size programs require for input include:

• Choose Type I error (alpha)
• Choose Power
• Choose clinical outcome variable and effect size (difference between means, proportions, survival times, regression parameters)
• Variation estimate
• Allocation ratio

Clinical outcome measures

Clearly describe the clinical outcomes that will be analyzed to the statistician. The variable type ( Table 4 ) and distribution of the primary outcome measurement must be defined before sample size and power calculations can proceed. The sample size estimates are mainly needed for the primary outcome. However, providing power estimates for secondary outcomes is often helpful to reviewers.

Variable types and derivations to be described in the statistical analysis plan

Effect size

As an example, suppose a parallel group study is being designed to compare systolic blood pressure between two treatments and the investigators want to be able to detect a mean 10 mm Hg difference between groups. This 10 mm Hg difference is referred to as the effect size, detectable difference, or minimal expected difference.

How is the effect size determined?

Choose an effect size that is based on clinical knowledge of the primary endpoint. A sample size that ‘worked’ in a published paper is no guarantee of success in a different setting. The selected effect size is unique to your study intervention, the specific type of participants in your study sample, and perhaps an aspect of the outcome measurement that is unique to your clinic or laboratory. 4

The investigator and statistician examine the literature, the investigator’s own past research, or a combination of the above to determine a study effect size. To investigate the difference in mean blood pressure between two treatments, the effect size options might be 2 mm Hg, 6 mm Hg, 10 mm Hg or 20 mm Hg. Which of these differences do you need to have the ability to detect? This is a clinical question, not a statistical question. Effect size is a measure of the magnitude of the treatment effect and represents a clinically or biologically important difference. Choosing a 20 mm Hg effect size yields a smaller sample size than a 10 mm Hg effect size since it is easier to statistically detect the larger difference. However, an effect size of 10 mm Hg or smaller magnitude may be more a realistic treatment effect and less likely to result in a flawed or wasted study.

Variation estimates for sample size calculations

In addition to effect size, we may need to estimate how much the outcome varies from person to person. For continuous variables, the variation estimate is often in the form of a standard deviation. If the hypothesized difference in systolic blood pressure is an effect size of 10 mm Hg, a study with a blood pressure standard deviation of 22 mm Hg will have lower power than a study where the standard deviation is 14 mm Hg. For a continuous outcome such as blood pressure, a measure of the variation is another part of the formula needed to compute the sample size. An estimate of variation can be derived from a literature search or from the investigator’s preliminary data. Obtaining this information can be a challenge for both the clinical investigator and statistician.

Table 5 shows sample sizes scenarios for detecting differences in blood pressure when comparing two treatments based on a t-test. A standard deviation of 14 mm Hg is chosen to estimate the variation. Sample sizes are calculated for power of 0.80 and 0.90 at the two-sided 0.05 significance level. Notice that the smaller effect sizes require a larger sample size and that the sample size increases as the power increases from 0.80 to 0.90.

Scenarios for choosing sample size

Determining a reasonable and affordable sample size estimate is a team effort. There are practical issues such as budgets or recruitment limitations that may come into play. A too large sample size could preclude the ability to conduct the research. The research team will assess scenarios with varying detectable differences and power as seen in Table 5 (calculations performed using PS power 5 available at the website < http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/PowerSampleSize >). Typically a scenario can be worked out which is both clinically and statistically viable.

The elements of sample size calculations presented here pertain to relatively simple designs. Cluster samples or family data need special statistical adjustments. For a longitudinal or repeated measures design, the correlation between the repeated measurements is incorporated into the sample size calculations. 6 , 7

Do all studies need sample size and power estimates?

Pilot studies.

Pilot studies may not need a power analysis since they are more about testing the protocol than testing a hypothesis. 8 Sometimes there are no preliminary data and thus pilot data must be obtained to provide estimates for designing for a more definitive study. However, calling a study a pilot study to avoid power analyses and to keep the sample small is misrepresentation. 8

Sample size calculations are necessary when the study goal is precision instead of power. The goal may be to describe the precision of a proportion or mean or other statistic that is to be estimated from our sample. Precision in this context is based upon finding a suitably narrow confidence interval for the statistic of interest, such that the lower and upper limits of the confidence interval include a clinically meaningful range of values. We may want to know how many subjects are required to be 95% confident that an interval contains the true, but unknown, value. For example, how many subjects are needed for 10% precision if we expect a 30% allele prevalence in a genetic study? Instead of power, we estimate the sample size for the desired precision based on a single proportion of 0.30 and summarize by stating “With 80 subjects, the precision for a 30% allele prevalence rate is approximately 10% (95% confidence interval: 21% to 40%).” If greater precision is desirable then the sample size is increased accordingly.

Accounting for attrition

Withdrawal and dropout are unwelcome realities of clinical research. Missing data in clinical trials or repeated measurement studies are inevitable. Consider missing data issues when designing, planning and conducting studies to minimize missing data impact. Sample size estimates are finalized by adjusting for attrition based upon the anticipated number of dropouts.

Randomization plan

Random allocation of subjects to study groups is fundamental to the clinical trial design. Randomization, which is a way to reduce bias, involves random allocation of the participants to the treatment groups. If investigators compare a new treatment against a standard treatment, the study subjects are allocated to one of these treatments by a random process. A general description of the randomization approach may be introduced in the clinical methods section of the proposal, for example, “Treatment assignment will be determined using stratified, blocked randomization”. Specific randomization details will need to be elaborated upon in the statistical methods section, including how the allocation procedure will be implemented, e.g., via computer programs, web site, lists, or sealed envelopes. If stratification is deemed necessary, include in the proposal a description of each stratification variable and the number of levels for each stratum, for instance, gender (male, female), diabetes (type 1, type 2). However, keep the number of strata and stratum levels minimal. 9 Discuss the advantages and disadvantages of the various allocation approaches with the study statistician.

Knowledge of the treatment assignment might influence how much of a dosage change is made to a study treatment or how an adverse event is assessed. Blinding or masking is another component of study design used to try to eliminate such bias. 10 In a double-blind randomized trial, neither the study subjects nor the clinical investigators know the treatment assignment.

Describe the planned blinding scheme. For example, “This is a double-blind randomized study to investigate the effect of propranolol versus no propranolol on the incidences of total mortality and of total mortality plus nonfatal myocardial infarction in 158 older patients with CHF and prior myocardial infarction.” Specify who is to be blinded and the steps that will be taken to maintain the blind. It is important that evaluators such as a radiologists, pathologists, or lab personnel who have no direct contact with the study subjects remain blinded to treatment assignments.

It may be impossible or difficult to use the double-blind procedures in some clinical trials. For example, it is not feasible to design a double-blind clinical trial for the comparison of surgical and non-surgical interventions. Or, blinding might not be completely successful; study personnel may be inadvertently alerted as to the probable treatment assignment due to the occurrence of a specific adverse event. If blinding is not feasible, offer an explanation for lack of blinding procedures in the research proposal.

STATISTICAL ANALYSIS METHODOLOGY

The statistical analysis methods for analyzing the study outcomes are to be carefully detailed. Specifying these methods in advance is another way to minimize bias and maintain the integrity of the analysis. Any changes to the statistical methods must be justified and decided upon before the blind is broken. 11 In the statistical analysis plan not only must the statistical hypotheses to be tested be described and justified but we also detail which subjects and observations will be included or excluded in each analysis.

Analysis data sets

Intention-to-treat analysis

It is crucial to define the primary sample of subjects analyzed in the reporting of clinical trial results. Defined in Table 6 , intention-to-treat (ITT) and per-protocol analyses are commonly reported in medical literature result sections. For a randomized study, intention-to-treat analysis is the gold standard for the primary analysis and the intention-to-treat principle is regarded as the most appropriate criteria for the assessment of a new therapy by the Food and Drug Administration and the National Institute of Health. 12 An intention-to-treat data set includes all randomized subjects, whether or not they were compliant or completed the study. Adhering to the ITT principle mirrors what occurs in clinical practice where a patient may discontinue a medication or miss a clinic appointment. This avoids biases that can result from dropouts and missing data. However, the missing data must not bias the treatment comparisons 13 , otherwise the statistics may not be valid. This type of bias could occur if the dropouts or missed study visits are related to a particular treatment group and are not observed equally across all of the treatments.

From ICH E9: Guidance for Industry - E9 Statistical Principles for Clinical Trials, U.S. Department of Health and Human Services, Food and Drug Administration, September 1998

A true intention-to-treat data set may not be attainable in all clinical trials. There might be no post-randomization or post-treatment data for a study subject who withdraws from the study at the initial study visit. Then the primary analysis might consist of all subjects who took at least one treatment dose or had at least one follow-up visit. 11 Anticipate these possibilities as the study is designed and specify in the statistical analysis plan which subjects and observations will comprise the “full analysis set”. Pre-specification of these data sets prior to statistical analysis is imperative.

Per-protocol analysis

It may be of clinical interest to plan an analysis set which consists of only ‘completers’ or ‘compliers’. A per-protocol analysis, defined in Table 6 , is more likely to be planned as secondary analyses. If the per-protocol analysis results are not consistent with the intention-to-treat analysis results, then closely examine the reasons behind any discrepancy.

Statistical analysis

The statistical analysis plan is driven by the research questions, the study design, and the type of the outcome measurements. The analysis plan includes a detailed description of statistical testing for each of the variables in the Specific Aim(s). If several Specific Aims are proposed, we write an analysis plan for each Specific Aim. Plan descriptive analyses for each group or planned subgroup. If subjects were randomly assigned to groups, it is expected that there will be a description of subject characteristics that include demographic information as well as baseline measurements or co-morbid conditions. Specify anticipated data transformations that may be needed to meet analysis assumptions and describe derived variables to be created such as area under the curve. Incorporate confidence intervals in the analysis plan for reporting treatment effects. Confidence limits are much more informative to the reader than are p-values alone. 14

Statistical details and terminology are not intended to be an obstacle for a young investigator. Instead this is where the statistical expert can be a valuable resource to help the investigators use the appropriate statistical methods and language that address the research hypotheses. Brief statistical analysis descriptions are shown in Table 7 for a randomized study and a longitudinal cohort study. In addition to the general methodology of Table 7 , we explain in the statistical methods section how statistical assumptions or model diagnostics will be evaluated. Describe the hypotheses to be tested with the corresponding statistical tests for the primary, secondary, and exploratory analyses. In the medical literature, statistical analyses such as chi-square and t-tests, analysis of variance, regression modeling, and various nonparametric tests are common. However, the statistician is happy to advise whether these traditional methods are appropriate for the research question at hand or if other approaches would be more suitable.

Statistical analysis plans

Statistics, like medicine, is a large and diverse field; hence statisticians have specific areas of expertise. Some proposals may require one statistician for the design and analysis of medical imaging studies and another statistician for design and analysis of a microarray study. Often a proposal specifies one statistician as the study statistician and another statistician to serve on a Data and Safety Monitoring Board.

Interim analysis

Conducting a planned interim analysis in an ongoing clinical trial can be beneficial for scientific, economic, and ethical reasons. 15 Formal interim analyses include stopping rules for terminating the study early if a treatment shows futility or clear benefit or harm. The termination of the estrogen plus progestin treatment arm of the Women’s Health Initiative clinical trial in 2002 16 when the treatment risks exceeded benefits demonstrates the strong clinical impact of interim analyses. However, interim analyses are not to be undertaken lightly. Taking unplanned repeated looks at accumulating data is problematic. First, it raises the multiple testing issue so that adjustments to control the overall Type I error rate are necessary. Second, the results can interfere with the conduct of the remainder of the study, creating bias. Pocock 17 and O’Brien & Fleming 18 authored the classic approaches for defining statistical stopping rules. The alpha spending function described by DeMets and Lan 19 provides some flexibility for the timing of interim analyses as well as controlling the Type I error rate. Clinical investigators must seriously consider what decisions might have to be made based upon interim analysis results and how this will affect an ongoing study.

OVERLOOKED OR INADEQUATELY DESCRIBED AREAS

Matching in case-control studies.

A weakness that often surfaces in sessions reviewing research proposals is an inadequate description of matching. Matching is commonly used in case-control studies by selecting for each case a control with the same value of the confounding variable. However, in our experience, the term “matching” is used too loosely. To a reviewer matching implies the recruitment of matched pairs. This may not be the intention of the investigators or the planned statistical analysis approach. A proposal that states that the participants will be matched according the gender, race/ethnicity, age, and body mass index would raise quite a few questions because ‘matching’ on all these variables would be quite difficult to achieve in practice. Often what the investigator really would like to insure is that the study groups will be balanced with respect to these characteristics. This is described as “frequency matching”. For continuous variables, such as age, the range that is considered a “match” needs to be specified. Indicate the target age range that is clinically comparable for your study, e.g., within 2 years or 5 years. Avoid matching on variables that are not known confounders as this may lead to loss of power. 20

Missing data prevention

It is well known that dropouts and certain missing data patterns can impact a study’s validity. Since statistical analyses cannot cure all problems associated with missing data, prevention is the best policy. To minimize dropouts and missed study visits, verify that the proposal has included a retention plan. Incorporate study procedures that may help to reduce the amount missing data, such as making regular calls to participants to better maintain contact as the study is underway. Every member of the research team must appreciate the need to reschedule or repeat key study visits or labs to the extent possible if the primary outcome measurement was not obtained. In order to obtain an analysis set that is consistent with the intention-to-treat principle, continue to schedule follow-up visits and collect primary outcome measurements for subjects who have discontinued their assigned treatment.

The integrity of the statistical analysis depends on the quality of the data. Obviously a study must contain high quality data (garbage in, garbage out), but steps to ensure this are frequently overlooked. Describe in the research proposal how data will be collected, de-identified, stored, and protected. It is vital that the clinical research team becomes skilled at data management. Meet with a database expert early to discuss the design of a database and related forms and involve the statistician in the review of the forms. Development of the proper data forms and database prior to study activation is essential.

We have presented guidance to be considered when developing the statistical plan in proposals for clinical and translational research. All these approaches have the common theme of eliminating or reducing bias and improving study quality. Planning the statistical methodology IN ADVANCE is crucial for maintaining the integrity of clinical research. We hope we have conveyed that developing the statistical methods for a research proposal is a collaborative effort between statistical and clinical research professionals.

Writing the statistical plan is a multidisciplinary effort. Both the clinical investigator and statistician on the research team need to carefully review the final product and ensure that the science and statistics correspond correctly. Just as a statistician who can understand the clinical aspect of the research is particularly advantageous, endeavor to learn all you can from the statistical expert. Ask the statistician to explain the rationale of the statistical methodology so you can defend the statistical plans without the statistician at your side. The clinical investigator may not have to know how to perform complex analyses but does need to understand the general statistical reasoning behind the proposed statistical design and analysis. When clinical investigators have a basic proficiency in statistical methodology, not only are collaborations with statisticians more dynamic and fruitful, but the potential to develop into a strong, independent clinical investigator and mentor increases. This leads to the design and execution of more efficient and advanced research, increasing the productivity of the entire research team.

Statistical Resources and Education

What if the researcher does not have funding to support a biostatistician? One option is to include a biostatistician as a co-investigator in your grant proposal to cover salary and supplies needed to implement the statistical methods described in the grant. Hopefully there is a department or division of Biostatistics or related field at your or a nearby institution. If not, long distance collaborations can succeed via conference calls and email. The American Statistical Association (ASA) has an ASA consulting section < http://www.amstat.org/sections/cnsl/ > where a clinical investigator can get assistance in finding a statistical consultant.

Some useful statistical websites for general statistical information and definitions include “The Little Handbook of Statistical Practice” < http://www.tufts.edu/~gdallal/LHSP.HTM >; “HyperStat Online Statistics Textbook” < http://davidmlane.com/hyperstat/index.html >; WISE Web Interface for Statistical Education < http://wise.cgu.edu/index.html >. Clinical trial statistical guidelines are documented in the International Conference on Harmonisation (ICH) Guidance for industry: E9 Statistical principles for clinical trials < http://www.fda.gov/ >. 11

As of September 2009, 46 medical research institutions in the United States have been granted a Clinical and Translational Science Award (CTSA, < www.ncrr.nih.gov/crctsa >). When the CTSA program is fully implemented, it will support approximately 60 centers across the nation. Some CTSA awardees offer biostatistical collaboration or institutional pilot grants for early career clinical investigators in need of statistical expertise. Many of these research centers offer Biostatistics courses or seminar series that are specifically designed for clinical researchers. This paper evolved from a CTSA course, “Clinical Research from Proposal to Implementation”, taught at the University of Texas Southwestern at Dallas. Take advantage of any such course offerings and resources.

A successful research proposal requires solid statistical methodology. The written statistical methods section is the result of teamwork between the clinical investigators and statisticians. Collaborating with a statistician early and often will help the study proposal evolve into a strong application that increases opportunities for scientific acceptance and funding for conducting important clinical research studies.

Acknowledgments

Grant support: NIH CTSA grant UL1 RR024982

What is the average age of both males and females upon death, who are buried at Mt. Vernon Cemetery? By using a random sample gathering, we will use the dates on randomly selected tombstones and will thereby form a confidence statement on the average age death of males and females at the cemetery. We can also compare the data of males vs. females. We will sample 5% of the headstones each for both sexes from already labeled six sections out of all the headstones in the cemetery. We will count, categorize, map, and assign all headstones with a number (first males, then females) and use a random number table to determine the 5% of each section that will be recorded from the population. As with any survey, there is always a chance of error. There is a possibility of encountering a worn headstone, misreading, wrong dates, unmarked headstones, problems recording data, and, of course, the inevitable human error. To deal with any sampling errors we will of course randomly pick another grave if the one that is selected happens to have any of the above mentioned situations. After collecting and organizing the data, we believe the average age of death for both males and females in Mt. Vernon Cemetery will be between 50 and 70 for males, and 60 and 80 for females. Ultimately, we believe that women had a longer life span than men on average. For this survey, we will not need permission from our instructor or from any security of the Mt. Vernon Cemetery. Academia.edu no longer supports Internet Explorer. To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser . Enter the email address you signed up with and we'll email you a reset link. We're Hiring! Help Center RESEARCH PROPOSAL ON STATISTICAL ANALYSIS ON FACTORS AFFECTING ACADEMIC ACHEIVMENT OF FEMALE STUDENTS IN AMBO UNIVERSTIY (IN THE CASE OF COLLEGE NATURAL AND COMPUTATIONAL SCIENCE). Related Papers HIGHER EDUCATION IN INDIA Saraswati Raju International Res Jour Managt Socio Human This article consists of five sections. The second section deals about growth and development of higher education in India. The third section analyses of women in higher education. The fourth section analyses the Scheduled Caste in higher education and the last section ends with the concluding observations Farooq Shah A cross sectional analysis was formulated to explore the Pukhtun's societal dilemma i.e., female getting higher education (Dependent variable) with respect to sociocultural hindrances (independent variable) through perceptional based dynamics at Bacha Khan University Charsadda. A sample size of 306 female respondents was selected from total 1500 registered female students in 2020 as per Sekeran's Magic Table. Quota sampling technique was used for the distribution of sample size among the selected categories of respondents. A three point Likert scale structured questionnaire encompassing all the study attributes was used after pre-testing. Furthermore, descriptive and inferential statistics was used for the analysis of data. Alike male cohorts the pursuit of higher education by females is the need of the twenty first century whereby they may have the probability to positively utilize it for economic gains, Socialization of children's and development of her societies. In the present era with almost many opportunities of pursuing female higher education parents are still least interested in female higher education, due to the harassment and exploitation cases towards them by teachers, classmates and educational administration. Pakistan Review of Social Sciences Sheharyar Khan The literacy rate is directly proportional to the development of a society. Pakistan lags behind other countries of the region in educating its masses. But since society is patriarchal, women face more problems than men in acquiring education. In this research, the prime objective was to find the socio-cultural factors that could become a barrier in acquiring higher education of women. Parental attitudes regarding the importance of educating girls may contribute to the education gender gap in rural areas. This research analyses the data collected from female students pursuing higher education Rawalpindi and Islamabad. Mainly socio-culture factors are highlighted in this research. owusu boakye , Cano Amaya Science, Technology, engineering, and mathematics (STEM) are broadly viewed as important to the national economy. Interest about America's capacity to be competitive in the global economy has prompted a number of calls to take action to reinforce the pipeline into these fields (National Academy of Sciences, Committee on Science, Engineering and Public Policy, 2007; U.S. Government Accountability Office, 2006; U.S. Bureau of Education, 2006; Hill, C., Corbett, C., St. Rose, A., & American Association of University, W. (2010). This is also true in Ghana. In 1957, “Ghana nursed the dream of rapid social and economic development using knowledge and tools derived from Science and Technology” (Ministry of Environment, Science and Technology, 2010). To strengthen or reinforce the pipeline into these fields, it is imperative to strengthen the number of female representatives in STEM programs. As many females drops out of STEM programs and also avoid pursuing STEM programs and degrees in high school and college respectively, there is a need to inquire why there a few or no role models and influential people in the lives of these female students in middle and high schools. This paper will build on a previous exploratory study on the influences and motivators of students when selecting a STEM academic program in secondary education. The study focuses on identifying influential people or concepts in female students decision to select academy/academic focus. Ayida Anjum Manika Kamthan Education is an ornament in prosperity and a refuge in adversity. — Aristotle Human Development Index engulfs all the socio-economic indicators of the society’s progress. Education is one of its most important factors. The Right to Education Act talks of the compulsory primary education. The higher education has been overpowered by the long cherished goal of ‘universal elementary education’. It is now widely accepted that higher education has been critical to India’s emergence in the global knowledge economy. Yet, it is believed that a crisis is plaguing the Indian higher education system. While, the National Knowledge Commission (NKC) set up by the Prime Minister calls it a ‘quiet crisis’, the Human Resource Minister calls higher education ‘a sick child’. The recent policies of the Government also favour the diversion of resources from higher to primary level of education and insist the full cost recovery from students even in public higher education. In the wake of economic reforms and privatization of the education there have been steep cuts in the public budgets for higher education, severely impairing the growth of higher education. Rather than pragmatism, it is populism, ideology and vested interests that drive public policy. It has been squarely ignored that the success of the economic reforms depends on the competence of human capital. The higher education institutions play an important role in setting the academic standard for primary and secondary education. In the 10th Five Year Plan Government emphasized on the self financing of the higher education institutions, which advocated the hike in the fees also. Thus, student fee and the student loans were developed as the cost recovery mechanisms. There mechanisms cause inequity because of their inherent weaknesses. Women constitute more than half of the population. When majority of the population remain deprived of higher education then we should be ready to experience its effects on the HDI of the country. The problem with HDI is this that it includes ‘literacy’ and not the ‘education’ as one of its indicators. The reform in the indicators of the human development is long overdue. Student loan for women is regarded as the negative dowry. UNESCO in 1998 emphasized the importance and need of higher education for women. Women lag behind man in higher education due to several reasons. In the following paper I shall elaborate on the fact that the financing strategy even under economic reforms seems to be developing one level of education at the cost of another, furthering the imbalances among different levels of education. Women are doubly jeopardized since they suffer the ignorance both of the government and the society at large Moreover, a Gender Budgeting Cell is needed for gender responsive budgeting initiatives in the higher education financing. It is urgent to realize the principle which UNESCO gave in 2000 that ‘higher education is no longer a luxury; it is essential to national, social and economic development”. There is urgent need to reform the public policies so as to make higher education more accessible to women Economic constraints to female higher education In Pukhtun Society Younas Khan The present study entitled economic constraints to female in getting higher education was conducted in union council balamabat district Dir lower Pakistan, to explore the economic anomalies which affect female higher education negatively. A sample size stood of 375 was selected by using purposive sampling techniques. The data was collected from both sexes through a well designed data collection tool questionnaire. Frequency and percentage distribution and chi square test was used to ascertain the association between dependent 'female higher education' and independent variable 'economic constraints' by using SPSS software. The study found that, a highly significant association (p=0.000) was found between dependent and independent variables indicators, the prevalence of poverty; lack of scholarships and loan by the government; inadequate budget allocation; expensive educational system and economic supremacy of male members of a society over women negatively affects women higher education. An immediate steps up is the order of the day by the government to increase the Prof Ngozi Agu For two decades now, there has been a heightened interest on gender equity in educational access. This interest is stimulated by the realization that one of the most effective strategies for promoting economic and social development in developing countries is education for all. In recognition of the positive impact of girl-child education, various organizations (UNICEF, UNESCO, CEDAW, CIDA, FAWEN ) have mounted many intervention programs and campaigns aimed at closing the wide gender gap in access to and achievement in education in Africa. A situation assessment and analysis on gender enrolment status in different countries by UNICEF in 2003 indicated that significant gender disparities still exist in many African countries. Though Nigeria made meaningful progress in ensuring gender equity in this area at the primary education level with a gender gap ratio of only 5 percent, however, being a highly patriarchal society, home and societal roles are still gender stereotyped. This is reflected in the admissions into different higher education courses in the universities. This paper assesses the gender status in enrollment into different faculties in a south eastern university in Nigeria. Enrollment status by male and female students into arts and science based courses offered in this university from 2008 to 2011 was assessed. Four research questions guided the study. Results indicated that in spite of the profuse efforts made so far to bridge the gender gap in education access in Nigeria, many higher education courses are still being construed as either masculine or feminine. Evidence of this gender gap, it is hoped, will sensitize the government, educational institutions and the general public on the current gender situation in human capital empowerment for necessary interventions. Euro Asia International Journals Abstract Gender-based discrimination in education is both a cause and a consequence of deep-rooted disparities in society. Poverty, geographical isolation, ethnic background, disability, traditional attitudes about their status and role all undermine the ability of women and girls to exercise their rights. Harmful practices such as early marriage and pregnancy, gender-based violence, and discriminatory education laws, policies, contents and practices still prevent millions of girls form enrolling, completing and benefiting from education. This paper deals with gender equity in higher education in India. It outlines the Indian higher education scenario. This paper makes a special note on gender wise students’ enrolment in India, discipline wise enrolment, enrolment in major research disciplines and gender distribution. This paper concludes with some interesting findings along with policy suggestions. Loading Preview Sorry, preview is currently unavailable. You can download the paper by clicking the button above. The European Green Deal Find out what progress the von der Leyen Commission has made so far with the European Green Deal towards becoming climate-neutral by 2050. Striving to be the first climate-neutral continent Climate change and environmental degradation are an existential threat to Europe and the world. To overcome these challenges, the European Green Deal will transform the EU into a modern, resource-efficient and competitive economy, ensuring: no net emissions of greenhouse gases by 2050 economic growth decoupled from resource use no person and no place left behind The European Green Deal is also our lifeline out of the COVID-19 pandemic. One third of the €1.8 trillion  investments from the NextGenerationEU Recovery Plan, and the EU’s seven-year budget will finance the European Green Deal. The European Commission has adopted a set of proposals to make the EU's climate, energy, transport and taxation  policies fit for reducing net greenhouse gas emissions by at least 55% by 2030 , compared to 1990 levels. More information on  Delivering the European Green Deal . Discover the European Green Deal visual story 12 March 2024 - The Commission has published a Communication on managing climate risks in Europe that sets out how the EU and its countries can implement policies that save lives, cut costs, and protect prosperity. It comes as a direct response to the first-ever European Climate Risk Assessment by the European Environment Agency. It also addresses the concerns that many Europeans have following last’s year record temperatures and extreme weather events. The Commission is calling for action from all levels of government, the private sector and civil society to improve governance and tools for climate risk owners, manage risks across sectors and set the right preconditions to finance climate resilience. Key figures Featured initiatives. Related links Share this page Donald Trump has a small but clear lead over Joe Biden Likely range Jump to state forecasts Chance of being the state that decides the election. Overall chance of winning Without this state Methodology The Economist ’s model of America’s presidential election estimates each major candidate’s chances of winning each state and the overall electoral college. Developed with a team of scholars at Columbia University, the forecast combines national and state-level polls with fundamental data about the state of the economy, historical voting patterns and the demographics of each state to predict the likelihood of various outcomes of the race. The model does this by constructing thousands of scenarios, each one containing different vote shares in each state and different values for the impact of polling biases and other characteristics. The model is more likely to generate scenarios that are closer to matching the polls and fundamental data it has been given. The win probabilities presented here represent the share of these scenarios won by each candidate. For more details on exactly how the model accomplishes this and the thinking behind its design, read the full methodology . Find a Program Find A Contractor 2024 Announcements 2023 Announcements 2022 Announcements 2021 Announcements Social Media Press Release Email List New Large-Scale Renewable Energy Solicitation Announced To Deliver Clean Electricity Across The State Final proposals for large-scale land-based renewable energy projects due in august 2024. June 20, 2024 Governor Kathy Hochul today announced a new large-scale renewable energy solicitation to deliver clean electricity to New Yorkers. Building on New York’s 10-Point Action Plan , this solicitation seeks proposals for the development of new large-scale land-based renewable energy projects which are expected to spur billions of dollars in clean energy investments and create thousands of family-sustaining jobs in the State’s green economy. Today’s announcement supports progress toward achieving the State’s Climate Leadership and Community Protection Act goal to obtain 70 percent of New York’s electricity from renewable sources by 2030. “New York is building a clean energy economy that will allow us to drastically lower emissions while creating thousands of new good-paying jobs, boosting billions of dollars in economic growth, and spurring an injection of private investment into our local communities," Governor Hochul said . “Once selected, these projects will help accelerate our mission to power our state with affordable, reliable, zero-emission electricity for the benefit of all New Yorkers.” The competitive solicitation, administered by the New York State Energy Research and Development Authority (NYSERDA), is the latest in a planned series of procurements of land-based large scale renewable projects. As part of this solicitation, NYSERDA has included key provisions from the latest rounds of renewable energy procurements such as inflation indexing, labor provisions, stakeholder engagement requirements, new requirements emphasizing the importance of climate resiliency in project design, disadvantaged community commitments, agricultural land preservation, and related priorities to maintain the policy objectives introduced in prior solicitations to ensure an equitable energy transition. These elements are outlined within the solicitation documents and are designed to support the development and construction of numerous mature, late-stage renewable energy projects seeking to commence operation in the near term. NYSERDA President and CEO Doreen M. Harris said , “By advancing land-based renewable energy projects, New York is expeditiously moving our state forward as a leader in the transition to reliable and clean energy. NYSERDA remains committed to strengthening our renewable energy pipeline and delivering increasing amounts of renewable electricity to further bolster our grid of the future.” The process for submitting proposals into the land-based renewables solicitation will be conducted in two steps, with eligibility requirements due on July 15, 2024 , to confirm that interested projects are eligible to bid, and final proposals due on August 8, 2024 . More details on the land-based renewable energy solicitation are available on the Large-Scale Renewables Solicitation page  on NYSERDA’s website. Conditional award notifications to selected proposers are expected in September 2024. New York State Department of Labor Commissioner Roberta Reardon said , “New York's clean energy sector is not just about creating a sustainable environment; it's also about building a robust and resilient workforce that can thrive in the green economy. Under Governor Hochul's leadership, initiatives like this large-scale renewable energy solicitation are vital in driving economic growth, fostering innovation, and providing thousands of family-sustaining jobs.” New York State Department of Environmental Conservation Interim Commissioner Sean Mahar said , “Through Governor Hochul’s leadership, New York State continues to advance its strategic efforts to meet our renewable energy targets under the Climate Leadership and Community Protection Act and create the clean energy economy of the future. Today’s announcement demonstrates the State’s commitment to expanding large-scale wind and solar projects and reduce our reliance on fossil fuels, helping to ensure a cleaner and healthier environment for future generations.” New York State Department of Agriculture and Markets Commissioner Richard A. Ball said , “Today’s announcement of new large-scale renewable energy solicitation is a crucial step in New York’s transition to clean energy, which will preserve our natural resources and help New York meet its ambitious climate goals. With key provisions included for agricultural land preservation, NYSERDA’s 10-Point Plan will help the State provide a foundation for a greener economy while also ensuring we are protecting our farmland.” State Senator Kevin Parker, Senate Energy and Telecommunications Chair said , “Governor Hochul's announcement of the new large-scale renewable energy solicitation marks a significant step forward in New York's commitment to a sustainable future. By accelerating our transition to wind and solar power, we are not only advancing towards our ambitious Climate Act goal of 70 percent renewable electricity by 2030, but also fostering economic growth and creating green jobs across the state. This initiative reaffirms New York's leadership in combating climate change and sets a powerful example for other states to follow." State Senator Peter Harckham said , “Thank you, Governor Hochul, for spearheading this solicitation to advance New York’s clean energy goals. The Executive and Legislature are in lockstep on building a sustainable future through clean renewable energy. It is important to note that a kilowatt of clean energy is now cheaper to produce than a kilowatt of carbon-based energy. With these large-scale renewable energy projects, we are addressing climate change, saving ratepayers money and creating new green jobs.” Assemblymember Deborah Glick said , “As the summer heat is already upon us, nothing could make it clearer that we have no time to lose in generating more of our electricity from renewable sources. I applaud Governor Hochul for pursuing an aggressive plan to move us away from our dependency on fossil fuel generated electricity. New York State should continue to lead and with the Governor’s commitment we will see the transition to a cleaner environment by the expansion of renewable energy.” Alliance for Clean Energy New York Executive Director Marguerite Wells said , "Private renewable energy developers are ready and willing to invest billions of dollars into New York, providing jobs and tax revenue for our local municipalities. We expect numerous quality responses to this RFP, and we look forward to NYSERDA awarding projects that will be built expeditiously to bring benefits to New Yorkers as soon as possible.” New York League of Conservation Voters President Julie Tighe said , "As we enter what is expected to be another summer with record breaking heat and air quality alerts, the urgent need to tackle the climate crisis has never been more evident. It’s time to transition off of fossil fuels and deliver clean energy, and this solicitation will help do just that. We applaud Governor Hochul and NYSERDA on this progress, because more land-based wind and solar energy projects mean fewer greenhouse gas emissions and better air quality for New Yorkers." New York State AFL-CIO President Mario Cilento said , “Today’s announcement is an important step toward achieving New York’s clean energy goals. We applaud Governor Hochul and NYSERDA for ensuring the projects will be subject to precedent-setting labor standards and protections. We look forward to working together to ensure maximum application of those standards as well as domestic and New York content requirements and preferences so that we create family-sustaining careers while building New York’s clean energy future.” New York State Building Trades President Gary LaBarbera said , “As New York continues to pursue the energy goals set out by the CLCPA, we must continue to push forward large-scale wind and solar developments that generate thousands of family-sustaining union careers and economic stimulus in our local communities. We applaud Governor Hochul for continuing to push forward these initiatives that will support the delivery of reliable, renewable energy to more New Yorkers and improve the living conditions in our state for generations to come. Our members look forward to having the opportunity to contribute to these projects and pursue the paths to the middle class they pave for them.” Natural Resources Defense Council Director Jackson Morris said , “The launch of the 2024 solicitation process for new large-scale renewable energy projects, with proposals due in August 2024, builds on the momentum from the successful offshore wind awards for Empire Wind 1 and Sunrise Wind and provides an important opportunity to replace canceled projects so that New York stays on track to meet our ambitious target of 70% renewable electricity by 2030. Accelerating these renewable projects underscores New York’s commitment to a clean energy future and will bring cleaner air, better jobs, and a healthier environment for all New Yorkers.” American Clean Power Director of Eastern State Affairs Director Moira Cyphers said , “We commend NYSERDA for their responsiveness and proactive efforts to keep New York State's clean energy goals on track. Governor Hochul's leadership is pivotal in driving significant progress to expedite procuring clean energy which will attract new investment opportunities and create well-paying jobs across the state.” Citizens Campaign for the Environment Executive Director Adrienne Esposito said , “Governor Hochul’s exciting announcement is another surge for New York’s renewable energy sector! We will meet the state’s renewable energy Climate Act goals only by advancing new large-scale wind and solar projects. This week’s heat wave in mid-June is another clear indicator of climate change impacts across New York caused by our continued reliance on dirty fossil fuels. We must transition our energy production and land-based wind and solar energy projects are a key component of that transition. Today’s announcement exemplifies the state’s commitment to providing clean affordable energy to all residents while combating climate change, bolstering the economy, and creating thousands of green jobs. New York’s clean energy future is looking bright.” New York Solar Energy Industries Association Executive Director Noah Ginsburg said , “As New Yorkers across the state grapple with extreme heat and rising electric bills, accelerating renewable energy deployment has never been more urgent. New York Solar Energy Industries Association applauds NYSERDA and Governor Hochul for their commitment to achieving the clean energy and equity mandates in the Climate Act. Scaling up solar deployment is foundational to New York’s energy transition, and our member companies and solar workforce are at the ready.” New York State's Nation-Leading Climate Plan New York State's climate agenda calls for an orderly and just transition that creates family-sustaining jobs, continues to foster a green economy across all sectors and ensures that at least 35 percent, with a goal of 40 percent, of the benefits of clean energy investments are directed to disadvantaged communities. Guided by some of the nation’s most aggressive climate and clean energy initiatives, New York is advancing a suite of efforts – including the New York Cap-and-Invest program (NYCI) and other complementary policies – to reduce greenhouse gas emissions 40 percent by 2030 and 85 percent by 2050 from 1990 levels. New York is also on a path to achieving a zero-emission electricity sector by 2040, including 70 percent renewable energy generation by 2030, and economywide carbon neutrality by mid-century. A cornerstone of this transition is New York's unprecedented clean energy investments, including more than $28 billion in 61 large-scale renewable and transmission projects across the State, $6.8 billion to reduce building emissions, $3.3 billion to scale up solar, nearly $3 billion for clean transportation initiatives and over $2 billion in NY Green Bank commitments. These and other investments are supporting more than 170,000 jobs in New York’s clean energy sector as of 2022 and over 3,000 percent growth in the distributed solar sector since 2011. To reduce greenhouse gas emissions and improve air quality, New York also adopted zero-emission vehicle regulations, including requiring all new passenger cars and light-duty trucks sold in the State be zero emission by 2035. Partnerships are continuing to advance New York’s climate action with more than 400 registered and more than 130 certified Climate Smart Communities, nearly 500 Clean Energy Communities, and the State’s largest community air monitoring initiative in 10 disadvantaged communities across the State to help target air pollution and combat climate change. Media Inquiries Executive Chamber, Phone:  518-474-8418, Ext.  n/a Email: [email protected] About the Hub Announcements Faculty Experts Guide Subscribe to the newsletter Explore by Topic Arts+Culture Politics+Society Science+Technology Student Life University News Voices+Opinion About Hub at Work Gazette Archive Benefits+Perks Health+Well-Being Current Issue About the Magazine Past Issues Support Johns Hopkins Magazine Subscribe to the Magazine You are using an outdated browser. Please upgrade your browser to improve your experience. 44 collaborative research teams receive Johns Hopkins Discovery Awards Winning projects, chosen from a record 286 proposals, include 148 individuals from across the university. By Hub staff report Creating DNA-based hydrogel bioinks with enhanced mechanical properties for advanced 3D bioprinting applications, such as smart bandages, biosensors, and water filtration membranes. Gaining a better understanding of how trust in the health care system is formed and how it influences patient behavior and outcomes, with the goal of identifying strategies to improve trust and, consequently, public health. Designing a novel influenza vaccine to overcome the challenges of immunosenescence and inflammaging in the elderly, which currently limit the effectiveness of seasonal influenza vaccines. These are among 44 multidisciplinary endeavors that have been selected to receive support this year from Johns Hopkins University's Discovery Awards program . Each project team is made up of members from at least two JHU entities who aim to solve a complex problem and expand the horizons of knowledge. Altogether, the winning project teams—chosen from a record 286 proposals—include 148 individuals representing 11 Johns Hopkins entities. "As society confronts challenges of increasing complexity, we require solutions that engage different disciplinary perspectives," JHU President Ron Daniels said. "This year's Discovery Awards recipients draw on the remarkable strengths of our faculty across our one university, forging new and impactful collaborations with the potential to improve health care, combat climate change, and harness the power of artificial intelligence." The Discovery Awards program was launched in early 2015 , as was the Catalyst Awards program for early-career researchers. Together the two programs represent a $45 million commitment by university leadership, in tandem with deans and directors of JHU's divisions, to faculty-led research. The Discovery Awards are intended to spark new interactions among investigators across the university rather than to support established projects. Teams can apply for up to $100,000 to explore a new area of collaborative work with special emphasis on preparing for an externally funded large-scale grant or cooperative agreement. "Cross-disciplinary collaboration is vital for solving society's greatest challenges, from developing innovative health technologies to confronting climate change," Provost Ray Jayawardhana said. "The Discovery Awards foster those crucial partnerships across Johns Hopkins, unleashing the creative potential of our scholars to drive transformative research. Congratulations to the 2024 awardees!" This year the Discovery Awards joined forces with the Hopkins Business of Health Initiative , Data Science & AI Institute , Institute for Assured Autonomy , OneNeuro Initiative , and Ralph O'Connor Sustainable Energy Institute to award additional seed funding to related projects. Awarded teams include faculty from computer science, environmental health & engineering, history, materials science & engineering, and research & exploratory development. The Discovery/DSAI co-funded project "Large Language Models (LLMs) for Knowledge Discovery in the Opioid Industry Documents Archive" brings together the schools of Engineering, Public Health, and Arts & Sciences to develop innovative methods for open-ended corpus analysis using LLMs to analyze the vast Opioid Industry Documents Archive (OIDA). The team aims to uncover key structural determinants of the crisis, such as marketing strategies, prescribing practices, and regulatory failures, while validating their approach by recreating codebooks and analyzing the robustness and consistency of the LLM outputs. The insights gained from this groundbreaking study have the potential to shed new light on the complex factors contributing to the opioid epidemic and inform policy decisions to address this pressing public health issue. "The Discovery Awards program leverages Hopkins's unique collaborative culture to support important research ideas at the interface of disciplines," says Denis Wirtz , vice provost for research. "Expert reviewers helped select the most meritorious ideas from groups of faculty in all divisions of the university, a tall order given the extremely high quality of the proposals this year." The full list of recipients and their projects is available on the Office of Research website. Posted in University News Tagged discovery awards Related Content 35 early-career faculty members earn Catalyst Awards You might also like, news network. Johns Hopkins Magazine Get Email Updates Submit an Announcement Submit an Event Privacy Statement Accessibility Discover JHU About the University Schools & Divisions Academic Programs Plan a Visit my.JohnsHopkins.edu © 2024 Johns Hopkins University . All rights reserved. University Communications 3910 Keswick Rd., Suite N2600, Baltimore, MD X Facebook LinkedIn YouTube Instagram Log in using your username and password Search More Search for this keyword Advanced search Latest content Current issue Anniversary BMJ Journals You are here Online First Tobacco endgame goals and measures in Europe: current status and future directions Article Text Article info Citation Tools Rapid Responses Article metrics http://orcid.org/0000-0002-8814-1021 Hanna Ollila 1 , http://orcid.org/0000-0001-9601-7330 Otto Ruokolainen 1 , http://orcid.org/0000-0002-6614-4782 Tiina Laatikainen 1 , 2 , http://orcid.org/0000-0003-3339-8441 Helena Koprivnikar 3 and JATC-2 WP9 co-authors 1 Department of Public Health , Finnish Institute for Health and Welfare , Helsinki , Finland 2 Institute of Public Health and Clinical Nutrition , University of Eastern Finland , Kuopio , Finland 3 National Institute of Public Health of the Republic of Slovenia , Ljubljana , Slovenia Correspondence to Hanna Ollila, Department of Public Health, Finnish Institute for Health and Welfare, Helsinki 00271, Finland; hanna.ollila{at}thl.fi The European Union (EU) aims for a tobacco use prevalence of less than 5% by 2040 with its Tobacco-Free Generation goal, aligning with the tobacco endgame approach. In the Joint Action on Tobacco Control 2 (JATC-2) -project, we examined adopted and planned endgame goals and measures as well as preparedness to counter tobacco industry interference in the process. We surveyed key informants in 24 out of 50 countries in the WHO European Region (19 of the 27 EU Member States, MS). Altogether, eight countries (7 EU MS) had official governmental endgame goals, and an additional six EU MS had similar proposals from government, civil society or research entities. Movement towards tobacco endgame was most evident in retail-oriented and consumer-oriented policies. These include restricting the sales of tobacco and related products and raising the age limit above 18 years. Product standards were used especially to regulate flavours but no measures to substantially reduce addictiveness were reported. Market-oriented measures that tap into industry profits were predominantly missing, and countries often lacked concrete tools to prevent industry interference. Respondents’ concerns around tobacco endgame were related to high smoking prevalence in some population groups, non-combustible and new nicotine products, cross-border marketing, political will, challenges with the existing regulations and industry interference. Results indicate both momentum and challenges in adopting and disseminating measures that facilitate achieving tobacco endgame goals. The EU goal can be used to advocate for national endgame goals and measures, and for the strengthened implementation of the WHO Framework Convention on Tobacco Control. Public policy Tobacco industry This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ . https://doi.org/10.1136/tc-2024-058606 Statistics from Altmetric.com Request permissions. If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways. WHAT IS ALREADY KNOWN ON THIS TOPIC In the tobacco endgame approach, the focus is shifted from controlling the tobacco epidemic to ending it by reducing use to a minimal level in the population with structural, political and social changes. In the European Union, this is supported by the recently launched Tobacco-Free Generation goal. Tobacco endgame is well aligned with the WHO Framework Convention on Tobacco Control, which encourages parties to implement measures beyond the convention to better protect human health and obliges them to adopt effective measures to prevent and reduce nicotine addiction besides tobacco consumption. WHAT THIS STUDY ADDS While several European countries already have governmental tobacco endgame goals or proposals towards these, there is substantial variation in their definitions, timelines and coverage of tobacco and nicotine products. Adopted and planned tobacco endgame measures centre around product-oriented, retail-oriented and consumer-oriented policies, such as product standards to reduce appeal, restricting sales and increasing the age limit above 18 years. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY Knowledge sharing facilitates the dissemination of tobacco endgame approach. More focus is needed on measures that can be expected to have a substantial impact on product availability, appeal and addictiveness. Concrete tools to prevent and counter tobacco industry interference are needed, as it is seen as a clear challenge in tobacco endgame. Introduction In the WHO European Region, encompassing 53 countries including 27 European Union (EU) Member States, 25% of adults use tobacco. 1 This prevalence ranks second highest among the WHO regions, with a relatively slow decline compared with other regions. In 2021, as part of Europe’s Beating Cancer Plan, the EU announced a ‘Tobacco-Free Generation’ goal for the region. 2 While the concept of tobacco-free generation originates in a proposal to limit tobacco sales by year born, 3 the EU goal is defined as less than 5% of the population using tobacco by 2040. The EU goal aligns with the tobacco endgame approach, where the focus shifts from controlling the tobacco epidemic to ending it by reducing use to a minimal level in the population with structural, political and social changes. 4 The EU goal is well justified under the WHO Framework Convention on Tobacco Control (WHO FCTC), which encourages parties to implement measures beyond the convention to better protect human health (Article 2.1) and obliges them to adopt effective measures and cooperate in developing appropriate policies to prevent and reduce tobacco consumption, nicotine addiction and exposure to tobacco smoke (Article 5.2b). 5 Several European countries have already set their national tobacco endgame goals prior to the EU goal. 6 We examine the current status of adopted and planned national goals and measures in the WHO European region, and how these reflect the EU goal among the Member States. We also examine how experts perceive the likelihood of adopting or achieving the endgame goal in their own country, and countries’ preparedness to counter tobacco industry interference in the process. In the Joint Action on Tobacco Control 2 (JATC-2) project, 7 Work Package 9 (WP9) is tasked to identify national tobacco endgame strategies and forward-looking tobacco control policies, to explore and exchange best practices in the development, implementation and evaluation of these strategies and policies, and to facilitate their development in the European region. The WP9 involves 21 partner organisations from 15 European countries (Belgium, Cyprus, Denmark, Finland, France, Greece, Hungary, Ireland, Italy, Lithuania, Norway, Portugal, Serbia, Slovenia and Spain), with the Netherlands collaborating. As part of this work, we surveyed key tobacco control informants in the WHO European region between 15 September 2022 and 13 January 2023. Participants Key informants consisted primarily of national WHO FCTC focal points, who are nominated by their country to participate in the official treaty reporting. Contacting them was made possible through assistance from the WHO FCTC Knowledge Hub on Surveillance and Convention Secretariat. In the absence of a functional contact with the focal point (eg, due to personnel changes), other national tobacco control experts were identified with assistance from JATC-2 partners and the WHO European Office for the Prevention and Control of Noncommunicable Diseases. We excluded Switzerland and Monaco due to lack of contacts, and the Russian Federation due to the suspension of research collaboration because of the war in Ukraine. From each country, one coordinated response was requested if the respondent engaged other stakeholders. The questionnaire gathered information and expert opinions on national-level policies and was, therefore, not subjected to an ethics approval. Respondents gave an informed consent on their participation. Responses were received from 24 of 50 countries (19 of 27 EU Member states), with response rates of 48% across the region and 70% within the EU. The respondents were from Austria, Azerbaijan, Belgium, Cyprus, Czechia, Denmark, Estonia, Germany, Finland, France, Hungary, Ireland, Italy, Lithuania, Luxembourg, the Netherlands, North Macedonia, Norway, Portugal, Serbia, Slovenia, Spain, Sweden and Uzbekistan. The majority of the respondents were officials from health ministries/departments/directorates in the government. One respondent was from the interior ministry, two from national authorities specialised in addictions or substance use and one from a public health institute. Respondents were contacted back in March 2023 for potential updates, which were received from Uzbekistan. The JATC-2 partners could further update the information on new national policies up to May 2024. Partner updates were provided by Belgium, Finland, France, Ireland, the Netherlands, Norway, Slovenia and Spain. Questionnaire The questionnaire assessed the existence of national tobacco endgame goals, their definition, the selected time frame, tobacco or nicotine products covered by the goals and the perceived likelihood of adopting/achieving these goals (from 0=very unlikely to 10=very likely). The reason for the selected response was asked. Furthermore, we inquired about adopted or planned endgame measures and measures to prevent industry interference ( table 1 ). The endgame measures for the questionnaire were identified from earlier reviews. 4 8 In WP9, harm reduction measures are outside the scope of work and were, therefore, not included in the questionnaire. The measures on tobacco industry interference were derived from screening the recommendations of the WHO FCTC Article 5.3 guidelines. Some additional measures of interest to WP9 partners were also added (marked with * in table 1 ). The questionnaire and more details of its development are available in the WP9 indicator compendium at www.jaotc.eu . 9 View inline Measures included in the JATC-2 WP9 questionnaire We describe adopted goals and measures based on respondent-provided details supplemented with publicly available information on the goals and measures (from, eg, governmental and EU websites). For plans or proposals, we disclose country names only if the information is publicly available to prevent industry interference. We present quotes from the experts’ open-ended responses. This article does not seek to present an exhaustive list of endgame goals and measures in Europe but provides examples and experiences, which can help draw an overview of their status and future directions. Tobacco endgame goals Official goals adopted or acknowledged by governments. Altogether eight countries reported official tobacco endgame goals ( table 2 ). These were divided into general population goals without subgroup targets and goals including certain generations or subgroups. Most of the countries are aiming for less than 5% prevalence of use, but three countries aim at no use at all in certain subgroups addressing children or pregnant women. Three countries define their prevalence goals specifically as daily use. All countries except Norway have set a target year between 2025 and 2040. The official definitions focus on smoking or tobacco use, except for three countries that also mention nicotine products or tobacco-related products. Some countries extend the scope of endgame compared with the main definition: Belgium and the Netherlands reported including all tobacco and non-pharmaceutical nicotine products, while France and Norway also reported including heated tobacco products (HTPs) under their smoking targets. Finland and Norway have integrated the endgame goal into the objective of the tobacco control law. Official tobacco endgame goals among the countries responding to the JATC-2 WP9 questionnaire Proposals from governmental bodies or other relevant organisations or entities (eg, NGOs, political parties, public health organisations) Altogether seven countries reported endgame proposals from their countries. In Denmark, the former government introduced a Nicotine-Free Generation goal where no one born since 2010 should start smoking or using nicotine products, 10 but this proposal has not progressed. A strategy for tobacco-free Germany by the German Cancer Research Center, supported by several NGOs and research entities, aims for <5% adult and <2% adolescent prevalence in tobacco and non-pharmaceutical nicotine use by 2040. 11 Additionally, the German government’s strategy for the Sustainable Development Goals contains a goal close to the common endgame prevalence level, namely, of 7% smoking prevalence among youth by 2030. 12 In Italy, scientific societies and independent scientists have allied to advocate for the development of a national tobacco endgame strategy. 13 In Spain, a new comprehensive plan for the prevention and control of tobacco for years 2024–2027 includes a goal to achieve <5% prevalence of daily use among 14–18-year olds. 14 Previously, public health organisations and civil society associations published an endgame declaration calling for a goal of <5% smoking prevalence by 2030 and 2% by 2040 in Spain. 15 Two other countries reported that an endgame proposal exists but is not yet publicly available. One was part of national health strategy discussions, where a goal in line with the EU goal has been proposed. From the second, no details were provided. Perceived challenges and opportunities in tobacco endgame Among the respondents from eight countries with official endgame goals, six provided a score for the likelihood of achieving their goal. On a scale of 0–10, the responses were either 6 (three countries) or 7 (three countries), reflecting moderately positive expectations. Concerns were expressed in relation to non-combustible and new nicotine products, differences between population groups, industry interference, cross-border marketing and sales, sustaining the political will and challenges in estimating the impact of the measures ( table 3 ). Respondents’ reflections on the perceived likelihood of achieving their official governmental tobacco endgame goals (six countries, panel A), and on the perceived likelihood of adopting such goals in their country (12 countries, panel B). Among 12 of the 16 countries without an endgame goal who provided a score, the expectations of adopting such a goal in their own country varied greatly: from very negative 0–2 (five countries) and somewhat unsure 5 (three countries) to rather positive 7–8 (two countries). Two countries perceived the adoption very likely, scoring 10. Concerns among these countries related to lack of political will, industry interference and problems in current tobacco control processes, shifting the focus to the COVID-19 pandemic, and the current high use of tobacco and related products ( table 3 ). Some countries reported a preference for general addiction or non-communicable disease (NCD) prevention strategies over tobacco control strategies. Having previously established governmental prevalence reduction goals in a cross-cutting way was seen as a strength for moving towards an endgame approach. Tobacco endgame measures Independently of whether a national tobacco endgame goal exists, a few measures that can contribute to such a goal were already implemented to some extent. These are presented in table 4 according to the taxonomy set in table 1 and summarised below. Adopted and planned tobacco endgame measures and forward-looking tobacco control measures among the countries responding to the JATC-2 WP9 questionnaire Product-oriented measures The EU Tobacco Products Directive (TPD) and the delegated directive 2022/2100 prohibit characterising flavours in cigarettes, roll-your-own and HTPs, but some countries go beyond this to reduce product appeal with different product standards. Five countries had fully prohibited menthol as an additive that facilitates inhalation in combustibles, and seven countries had prohibited all or most flavours in e-cigarette liquids ( table 4 ). These measures were also planned in some countries, and Finland was processing regulation on nicotine pouch flavours. Plain packaging had been extended from tobacco products to e-cigarette packaging in three countries and was also considered for nicotine pouch packaging in two. Some countries had standardised or were standardising the appearance of individual cigarettes, nicotine e-liquids, e-cigarette refill containers and/or nicotine pouches. Health warnings on individual cigarette sticks were considered in Norway, which had also prohibited imports and sales of waterpipe tobacco, therefore partially addressing a ban on combustibles. The TPD allows Member States to prohibit a certain category of tobacco or related products if the Commission approves it after considering whether national provisions are justified, necessary and proportionate, and whether they constitute a disguised barrier to trade. Belgium has received approval to prohibit disposable e-cigarettes, and two other countries also have proposals to introduce such a ban. Two countries reported an authorisation scheme for novel tobacco products, where the government authorises or rejects market entry applications. Non-pharmaceutical nicotine products (other than e-cigarettes) are not under TPD and countries regulate their market entry independently. An authorisation scheme for novel nicotine products was reported by two countries. Two countries have prohibited nicotine pouches. One country reported considering a ban on products that do not fall into existing product categories or are placed on the market after a certain date, but no specification was available. Retail-oriented measures Some countries reported prohibiting or restricting tobacco or related product sales in retail types or locations related to minors, and Cyprus was planning to restrict points of sales near schools ( table 4 ). Broader restrictions were still rare. New stepwise sales reductions were adopted in two countries, and a substantial reduction in retailers was set to the strategy in Norway but without concrete proposals. Two countries limited tobacco sales to specialist shops, and one country was considering including also e-cigarette sales to these. Hungary has set numerical limits to the density of the specialist tobacco shops. Finland introduced high annual supervisory fees to retail license holders and has had a proposal to prohibit the granting of a retail license to temporary and mobile sales places. France supported the transition of tobacco retailers into other local shops and no longer selling tobacco. Consumer-oriented, market-oriented and other innovative measures Most of the proposed endgame measures in these categories were not in place or planned. Plans focused on consumer-oriented measures, mainly age limits of 20 or 21 years, where altogether six countries have had proposals to raise the age of sale above 18. Of these, Ireland already approved in May 2024 a proposal for legislation that will increase the age of sale of tobacco to 21, aiming to be the first EU country to do so. 16 In Norway, a tobacco-free and nicotine-free generation to those born in 2010 is envisaged in a national strategy, but decisions and details on its implementation are awaited. In Denmark, the new prevention agreement proposes prohibiting the import, purchase and possession of nicotine products that are illegal to market in the country. Sweden is utilising excise duty for curtailing industry to set its own retail prices. Five countries have a regulated market model where the state has a monopoly on tobacco sales. Preparedness to counter tobacco industry interference While many respondents referred to implementing Article 5.3 of the WHO FCTC, concrete tools to prevent industry interference were often missing. However, some examples of adopted measures were shared. These addressed legislative measures, lobbying registers, a code of conduct/procedure, public disclosure of necessary correspondences, disclosure of lobbying expenses, plans to better regulate production and industry reporting obligations, and ethical guidelines preventing state investments in the tobacco industry ( table 5 ). As for planned measures, three countries were developing guidelines on contact between the industry and governmental organisations, one country was planning to develop a transparency register of contacts between the tobacco industry and government, and another country for the disclosure of the records from necessary interactions. Regulations and measures to prevent tobacco industry interference among the countries responding to the JATC-2 WP9 questionnaire Our results indicate both momentum and challenges in adopting and disseminating measures that facilitate achieving the EU Tobacco-Free Generation goal of less than 5% tobacco use by 2040. Almost half of the 27 EU Member States either have already adopted a national tobacco endgame goal or have a proposal for such a goal from the government, civil society or research entities. Outside the EU in the WHO European Region, Norway reported an official tobacco endgame goal. While most of the countries with an official goal aim for a similar <5% prevalence level as the EU goal, the definitions of goals and their specifications in the government documents vary considerably. For some countries, this can also pose challenges in measuring the progress. In Ireland and Sweden, the target year of 2025 is approaching soon, calling for the first comprehensive evaluations of national tobacco endgame strategies in the region. Including tobacco endgame as an objective of tobacco control legislation—like in Finland and Norway—may provide sustainability behind changing governmental programmes or strategies and political will. In the EU, the Member States have benefitted from common minimum product standards set in the TPD. While several countries already go beyond the TPD to address attractiveness and appeal, no measures that would substantially reduce addictiveness were adopted or planned. To meet the <5% prevalence level by 2040, the TPD should be developed from this perspective in a forward-looking way. The EU has invested substantial effort and resources into the advisory mechanism for the prohibition of characterising flavours. 17 Yet a simplified, effective approach would be to follow the WHO FCTC Article 9 and 10 guidelines to prohibit the use of all ingredients that make tobacco products attractive, including flavouring agents. Furthermore, the EU-level nicotine limits for cigarettes could be lowered to make them less or non-addictive, leading to their gradual phase-out from the market. Based on the evidence, reducing nicotine content in cigarettes to very low levels could improve public health and have benefits across different population groups by decreasing the uptake of regular smoking, decreasing the amount smoked and increasing smoking cessation. 18 Introducing very low nicotine cigarettes on the EU level could be a balanced and justified measure considering the increased product supply caused by the continuous entrance of novel tobacco or nicotine products to the market. These novel products were mainly seen as challenges in tobacco endgame by the respondents, and several countries are already covering nicotine products such as e-cigarettes and nicotine pouches in their endgame goals or measures. This can be seen as a forward-looking approach to respond to tobacco industry strategies, which aim to increase product portfolio and profit, attract new customers and delay and distract from effective control policies. 19 Clear separation between measures to only reduce harm and measures to end the tobacco epidemic may help regulators and policymakers to understand and identify measures that are feasible and likely to produce substantial impact in their local context. The reported retail-oriented and consumer-oriented measures tended to focus on reducing the sales points by limiting sales to certain retailers and raising the age limit of sales above 18 years. For example, substantial stepwise reductions in retail outlets are beginning to be implemented in the Netherlands and in Belgium. Yet, most countries in the region would still need to introduce retail licensing to effectively control and reduce retail density. 20 In Finland, the licensing with high annual costs has gradually reduced the number of tobacco retailers to approximately a half. However, the number remains high and unequally distributed to more socioeconomically disadvantaged areas—reminding of the continued need to consider the impact of tobacco endgame measures in different population groups. 21 In Hungary, the introduction of state-owned specialist tobacco shops has decreased the density of tobacco shops by 85%, concurring with declining adolescent smoking. 22 The age limits that were under consideration focused on 20 or 21 years. In the European context, where no country yet has implemented an age limit above 18 years for tobacco, this measure could have a substantial impact considering most of the initiation occurs by the age of 20. 23 24 In Europe, Norway was first to publish in March 2023 a goal that children born since 2010 do not use tobacco and nicotine products, but its practical implementation is undecided. 25 The United Kingdom has then moved ahead by announcing in October 2023 that it will become an offence to sell tobacco products to anyone born on or after 1 January 2009. 26 Based on the evidence, the retail- and consumer-oriented measures, especially if combined, can be expected to have a notable impact on tobacco use prevalence and lead to health gains over time. 23 27 The EU goal can be used to support the development of similar national goals. Additionally, it can be used to bring the need for better implementation of the WHO FCTC to the political agenda, connected to the national work for NCD prevention and sustainable development goals. This can be beneficial especially in countries where adopting an endgame goal is not yet seen as feasible in the current tobacco control context. The implementation of the WHO FCTC as well as the capacity for tobacco control needs to be strengthened in Europe. 28 As part of this, countries should look into measures that tap into tobacco industry profits, which are mostly not even planned in the region. Together with the lack of concrete tools to prevent and counter industry interference, this enables the industry to mobilise resources for lobbying and distracting policymaking away from timely and effective measures. Industry interference was identified as a challenge both in adopting and achieving tobacco endgame goals. Better protection is needed even on the EU level, as shown in the recent European Ombudsman investigations. 29 Besides national actions, the EU-level investment and support for the enforcement of tobacco control, together with the regular revision of key directives and recommendations, are essential for achieving the EU goal. An interesting comparison can be found in food safety where the EU audits the application and effectiveness of the laws and controls and provides training to the responsible authorities. 30 Finally, the EU goal can be used to raise awareness of the tobacco endgame approach, leveraging support from civil society and the public. For instance, a study from Ireland showed low awareness but broad support for the local tobacco endgame goal. 31 In the Netherlands, key factors in accelerating tobacco control have been the genesis of a ‘Smoke-free Generation’ movement in the wider society, initiated by the three main national charities, combined with stricter adherence to Article 5.3 of the WHO FCTC and a comprehensive marketing ban. 32 In 2022, several European civil society associations launched a joint European Citizen’s Initiative calling for a broad range of measures including tobacco-free environments and ending the sale of tobacco and nicotine products to citizens born since 2010, but it did not reach enough signatories. 33 To facilitate the dissemination of measures that are likely to have a substantial impact within a reasonable timeframe, knowledge sharing between countries with different tobacco control contexts and approaches is needed. Multinational collaborations such as the JATC-2 can serve as platforms to share best practices and act as vehicles to overcome the barriers of lack of knowledge or political will. A great global opportunity for information exchange presents in the 11th session of the Conference of the Parties of the WHO FCTC in 2025, where an expert group established by the COP10 will present its report on Article 2.1 and forward-looking tobacco control measures. 34 The possibility of shifting the focus from controlling to ending the tobacco epidemic is an important message to convey to policymakers. Ethics statements Patient consent for publication. Not applicable. Ethics approval This study gathered only information on national-level policies and expert opinions related to these and was therefore not subject to ethics approval. Participants gave informed consent to participate in the study before taking part. Acknowledgments The authors want to thank all the respondents of the questionnaire. The authors are grateful for the support and contributions from all JATC-2 WP9 partners in the development of the questionnaire and provision of feedback to the analysis and reporting of the results as part of the project reporting and deliverable drafting. Further, the authors are grateful for the support from the WHO FCTC Knowledge Hub on Surveillance, the Secretariat of the WHO FCTC and the WHO NCD Office in identifying the contacts for the questionnaire. World Health Organization European Commission McDaniel PA , Ruokolainen O , Laatikainen T , et al Straarup MS , O’Donovan F , Lambrou A , et al Puljević C , Morphett K , Hefler M , et al JATC-2 WP9 partners Sundshedsministeriet The German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) 2021 Die Bundesregierung TOBACCO ENDGAME Ministerio de Sanidad Cuadrado García de U , Fernández Megina R , et al Government of Ireland, Department of Health Chaiton M , Kuipers MAG , Nuyts PAW , Willemsen MC , et al Pätsi S-M , Ollila H , et al Brys Z , et al Reitsma MB , Mullany EC , et al Government of Norway Department of Health and Social Care van der Deen FS , Cleghorn CL , et al González-Marrón A , Koprivnikar H , Tisza J , et al European Union Cosgrave EJ , Murphy E , et al Willemsen MC , ↵ Call to achieve a tobacco-free environment and the first European tobacco-free generation by 2030 . 2022 . Available : https://citizens-initiative.europa.eu/initiatives/details/2022/000005_en [Accessed 22 Apr 2024 ]. Algemene Cel Drugsbereid Ministry of Social Affairs and Health, Finland Tobacco Act Ministère de la Santé et de la Prévention Ministry of Health, Welfare and Sport Lov om vern mot tobakksskader (Tobakksskadeloven) - Lovdata . Available : https://lovdata.no/dokument/NL/lov/1973-03-09-14?q=1973-03-09-14 [Accessed 17 Oct 2023 ]. Republica Slovenija Regeringskansliet Government proposal to Parliament for an Act amending the Tobacco Act. 2024/0210/FI (Finland) . TRIS - Eur Comm 2024 . Available : https://technical-regulation-information-system.ec.europa.eu/en/notification/25788 The Danish Ministry of the Interior and Health National Addictions Authority Cyprus Collaborators Co-authors of the Work Package 9 of the Joint Action on Tobacco Control 2 (JATC-2) -project: Adrián González-Marrón (Group of Evaluation of Health Determinants and Health Policies, Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain), Alessandra Lugo (Department of Medical Epidemiology; Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy), Angeliki Lambrou (Directorate of Epidemiology and Prevention of Non-Communicable Diseases and Injuries, National Public Health Organization (NPHO), Athens, Greece), Anna Mar Lopez Luque (Grupo de Investigación en Control del Tabaco, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, (CIBERES), Madrid, Spain; Programa de Prevenció i Control del Càncer, Institut Català d'Oncologia, L'Hospitalet de Llobregat, Barcelona, Spain), Armando Peruga (Grupo de Investigación en Control del Tabaco, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain, Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, (CIBERES), Madrid, Spain; Centro de Epidemiología y Políticas de Salud, Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile), Biljana Kilibarda,(Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia), Cristina Lidón-Moyan (Group of Evaluation of Health Determinants and Health Policies, Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain), Daniela Alejandra Blanco-Escauriaza (Group of Evaluation of Health Determinants and Health Policies, Department of Basic Sciences, Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain), Dolors Carnicer-Pont (Grupo de Investigación en Control del Tabaco, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, (CIBERES), Madrid, Spain; Programa de Prevenció i Control del Càncer, Institut Català d'Oncologia, L'Hospitalet de Llobregat, Barcelona, Spain), Efstathios Papachristou (Directorate of Epidemiology and Prevention of Non-Communicable Diseases and Injuries, National Public Health Organization (NPHO), Athens, Greece), Elena Demosthenous (Cyprus National Addictions Authority, Nicosia, Cyprus), Emilia Nunes (General Directorate of Health, Ministry of Health, Lisbon, Portugal), Esteve Fernández (Grupo de Investigación en Control del Tabaco, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, (CIBERES), Madrid, Spain; Programa de Prevenció i Control del Càncer, Institut Català d'Oncologia, L'Hospitalet de Llobregat, Barcelona, Spain; School of Medicine and Health Sciences, Campus de Bellvitge, Universitat de Barcelona, L’Hospitalet de Llobregat, Spain), Giulia Carreras (Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy), Giuseppe Gorini (Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy), Helma Slingerland (Ministry of Health, Welfare and Sport, the Hague, the Netherlands), Judit Tisza (National Korányi Institute of Pulmonology, Budapest, Hungary), Lorenzo Spizzichino (Ministry of Health, Rome, Italy), Maria-Alejandra Cardenas (Ministry of Health and Prevention, Paris, France), Maria Karekla (University of Cyprus, Nicosia, Cyprus), Maurice Mulcahy (National Environmental Health Service, Health Service Executive (HSE), Galway Business Park, Dangan, Ireland), Milena Vasic (Institute of Public Health of Serbia “Dr Milan Jovanovic Batut”, Belgrade, Serbia), Salla-Maaria Pätsi (Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland), Silvano Gallus (Department of Medical Epidemiology; Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy), Sotiria Schoretsaniti (Directorate of Epidemiology and Prevention of Non-Communicable Diseases and Injuries, National Public Health Organization (NPHO), Athens, Greece), Zsuzsa Cselkó (National Korányi Institute of Pulmonology, Budapest, Hungary). Contributors Salla-Maaria Pätsi conducted initial analyses from the data. HO analysed the data for this manuscript and wrote the first draft. OR, TL and HK reviewed the first draft. HO developed and revised the following drafts as per the review and contributions from all other authors. All authors approved the final version of the paper. HO is responsible for the overall conduct of the study and the contents of this manuscript. Funding This work was supported by the European Union’s Health Program (2014-2020) under grant agreement N°101035968. The content of this document represents the views of the authors only and is their sole responsibility; it cannot be considered to reflect the views of the European Commission and/or the European Health and Digital Executive Agency (HaDEA) or any other body of the European Union. The European Commission and the Agency do not accept any responsibility for use that may be made of the information it contains. DCP, AML and EF are partly supported by the Ministry of Universities and Research, Government of Catalonia (grant number: 2021SGR00906) and thank the CERCA programme for institutional support to IDIBELL. Competing interests None declared. Provenance and peer review Not commissioned; externally peer-reviewed. Read the full text or download the PDF: 261 IMAGES Soc 490 week 3 proposal for statistical research project 12+ Research Project Proposal Outline Templates FREE 3+ Data Analysis Research Plan Samples in PDF Research Proposal How to Write: Detail Guide and Template 11 Research Proposal Examples to Make a Great Paper (PDF) Thesis Proposal: A Brief Introduction to Statistical Network VIDEO Creating a research proposal Statistical Research Project- Leanne Sopha Lecture 7: Writing a Grant Proposal or A Research proposal ស្ថិតិបែបពិសោធន៍ ស្ថិតិបែបពិសោធន៍ Day 2: Statistical Data Analysis using R Programming for Staff and Students of Makerere University COMMENTS Top 10 Statistical Analysis Research Proposal Templates ... The curated collection of the Top 10 Statistical Analysis Research Proposal Templates offers a valuable resource for researchers and scholars. These templates, real-world samples, and examples provide a solid foundation for crafting compelling research proposals. By harnessing these tools, researchers can streamline proposal creation, ensuring ... 75+ Realistic Statistics Project Ideas To Score A+ Statistics Project Ideas for High School. Let's find out the best statistics project ideas for high school that will help you to score good grades and showcase your skills:-. Evaluate the published reports and graphs based on the analyzed data and conclude. Use dice to evaluate the bias and effect of completing data. How to Write a Research Proposal Research proposal examples. Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We've included a few for you below. Example research proposal #1: "A Conceptual Framework for Scheduling Constraint Management". PDF Ap Statistics Research Project Part I: Guidelines for Project Proposal AP Statistics Research Project Part 1: Project Proposal - Grading Rubric discipline and impacts in society beyond the experiment (20 pts) topic as well as implications for potential findings from the research project. Substantial justification for the value of the research project Is established, with clear description of project goals and Introduction to Research Statistical Analysis: An Overview of the Introduction. Statistical analysis is necessary for any research project seeking to make quantitative conclusions. The following is a primer for research-based statistical analysis. It is intended to be a high-level overview of appropriate statistical testing, while not diving too deep into any specific methodology. PDF Formulating a statistical analysis plan as part of the project proposal Formulating a statistical analysis plan . as part of the project proposal To be properly assessed, a project proposal requires not only a research design, but also a general set-up of the statistical analysis plan, as it will provide a reliable estimate of the maximum number of animals needed. This gives a good idea of what efforts you are How To Write A Research Proposal Here is an explanation of each step: 1. Title and Abstract. Choose a concise and descriptive title that reflects the essence of your research. Write an abstract summarizing your research question, objectives, methodology, and expected outcomes. It should provide a brief overview of your proposal. 2. How to write a statistical analysis plan for research projects This is because it is difficult to work on a research project from start to end, if the research scope, aims, and potential pitfalls are not clear or undefined. Below, I have composed a short recipe for how to write a concise statistical analysis plan, which will be helpful towards starting a research project or writing a scientific research paper. Data Analytics Resources: Writing a Research Proposal A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take. Proposal Format. Step 1; ... This brings the focus back to your project. Next, your research design or methodology section will describe your overall approach, and the practical steps ... Tips for Writing a Statistical Analysis Plan In particular, we present tips for writing an excellent statistical analysis plan or biostatistical core for a biomedical or public health research grant with a primary focus outside of biostatistics. We will focus our attention on R01 research project grants and multi-project awards (e.g., P01, P30, P50, U19). Research: Writing effective statistical methodology for a research proposal The Journal of Investigative Medicine published an informative article titled "Bridging Clinical Investigators and Statisticians: Writing the Statistical Methodology for a Research Proposal." The introduction : "Clinical research is judged to be valid not by the results but how it is designed and conducted. The cliché of 'do it right or do ... Research Proposal Academic Research Proposal. This is the most common type of research proposal, which is prepared by students, scholars, or researchers to seek approval and funding for an academic research project. It includes all the essential components mentioned earlier, such as the introduction, literature review, methodology, and expected outcomes. Research Proposal Example (PDF + Template) Detailed Walkthrough + Free Proposal Template. If you're getting started crafting your research proposal and are looking for a few examples of research proposals, you've come to the right place. In this video, we walk you through two successful (approved) research proposals, one for a Master's-level project, and one for a PhD-level ... PDF DATA ANALYSIS PLAN •Data are random numbers. Plan accordingly. • Statistical analysis is the language of scientific inference. Expand your vocabulary. • Statistical analysis is harder than it looks. • Get help now, before you start writing. • Get help while you are writing. • Budget help for later. • When in doubt, call statistician. • When not in doubt, call statistician. Creating a Data Analysis Plan: What to Consider When Choosing INTRODUCTION. Statistics represent an essential part of a study because, regardless of the study design, investigators need to summarize the collected information for interpretation and presentation to others. It is therefore important for us to heed Mr Twain's concern when creating the data analysis plan. In fact, even before data collection ... Top 99+ Trending Statistics Research Topics for Students Have a look at some good topics for statistics projects:-1. Research the average height and physics of basketball players. 2. Birth and death rate in a specific city or country. 3. Study on the obesity rate of children and adults in the USA. 4. The growth rate of China in the past few years 5. Major causes of injury in Football Writing a Scientific Research Project Proposal Abstract: This is a brief (300-500 words) summary that includes the research question, your rationale for the study, and any applicable hypothesis. You should also include a brief description of your methodology, including procedures, samples, instruments, etc. Introduction: The opening paragraph of your research proposal is, perhaps, the most ... Bridging Clinical Investigators and Statisticians: Writing the A successful research proposal requires solid statistical methodology. The written statistical methods section is the result of teamwork between the clinical investigators and statisticians. Collaborating with a statistician early and often will help the study proposal evolve into a strong application that increases opportunities for scientific ... Research Projects in Statistics We can also compare the data of males vs. females. We will sample 5% of the headstones each for both sexes from already labeled six sections out of all the headstones in the cemetery. We will count, categorize, map, and assign all headstones with a number (first males, then females) and use a random number table to determine the 5% of each ... (PDF) STUDENTS' STATISTICS PROJECT PROPOSAL Horizon Research Publishing (HRPUB) Kevin Nelson. This paper describes a group project created for an introductory statistics course. The main idea of the project is to have groups of 2-3 students select a published journal article on a topic of their choice and then present the results of that article to their classmates. (Doc) Research Proposal on Statistical Analysis on Factors Affecting Task Time Title selection May 20-05-2014 Data collection May 24-26 Proposal writing May 27-29 Proposal submission June 03-06-2014 Proposal presentation June 05-06-2014 13 5. BUDGET BREAKDOWN STATIONARY BUDGET REQUIREMENT AND PRE- ANALYSIS BUDGET. PDF Statistics of Income—Joint Statistical Research Program Call for Proposals. Through its Joint Statistical Research Program (JSRP), Statistics of Income (SOI) seeks to enable the use of tax microdata by qualified researchers outside the Federal government. Such research can provide new insights and advance the understanding of the ways that existing tax policies affect individuals, businesses, and ... Proposal for Statistical Research Project 1.docx A realistic timeline for this research project because it should be anywhere between 2000 to 3500 words, and I would have to familiarize myself with the topic chosen and narrow down on that topic. Then I would have to do this by way of research from different sources like the school library or internet searches or may by just brainstorming a topic. . With everything that needs to be done when ... The European Green Deal The European Commission has adopted a set of proposals to make the EU's climate, energy, transport and taxation policies fit for reducing net greenhouse gas emissions by at least 55% by 2030, compared to 1990 levels.More information on Delivering the European Green Deal.. Discover the European Green Deal visual story Project 2025 Project 2025, also known as the Presidential Transition Project, is a collection of conservative policy proposals from The Heritage Foundation to reshape the United States federal government in the event of a Republican Party victory in the 2024 presidential election. Established in 2022, the project aims to recruit tens of thousands of conservatives to the District of Columbia to replace ... Trump v Biden: The Economist's presidential election prediction model Methodology. The Economist's model of America's presidential election estimates each major candidate's chances of winning each state and the overall electoral college.Developed with a team ... New Large-Scale Renewable Energy Solicitation Announced To ... Governor Kathy Hochul today announced a new large-scale renewable energy solicitation to deliver clean electricity to New Yorkers. Building on New York's 10-Point Action Plan, this solicitation seeks proposals for the development of new large-scale land-based renewable energy projects which are expected to spur billions of dollars in clean energy investments and create thousands of family ... 44 collaborative research teams receive Johns Hopkins ... Altogether, the winning project teams—chosen from a record 286 proposals—include 148 individuals representing 11 Johns Hopkins entities. "As society confronts challenges of increasing complexity, we require solutions that engage different disciplinary perspectives," JHU President Ron Daniels said. "This year's Discovery Awards recipients draw on the remarkable strengths of our faculty ... Tobacco endgame goals and measures in Europe: current status and future The European Union (EU) aims for a tobacco use prevalence of less than 5% by 2040 with its Tobacco-Free Generation goal, aligning with the tobacco endgame approach. In the Joint Action on Tobacco Control 2 (JATC-2) -project, we examined adopted and planned endgame goals and measures as well as preparedness to counter tobacco industry interference in the process. We surveyed key informants in ... assignment essay homework paper phd report review speech thesis