Show that you understand the current state of research on your topic.
The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.
One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.
Download our research proposal template
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.
Like your dissertation or thesis, the proposal will usually have a title page that includes:
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:
To guide your introduction , include information about:
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 already 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:
Following the literature review, restate your main objectives . This brings the focus back to your own 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.
? or ? , , or research design? | |
, )? ? | |
, , , )? | |
? |
To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasise again what you aim to contribute and why it matters.
For example, your results might have implications for:
Last but not least, 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 our free APA citation generator .
Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.
Here’s an example schedule to help you get started. You can also download a template at the button below.
Download our research schedule template
Research phase | Objectives | Deadline |
---|---|---|
1. Background research and literature review | 20th January | |
2. Research design planning | and data analysis methods | 13th February |
3. Data collection and preparation | with selected participants and code interviews | 24th March |
4. Data analysis | of interview transcripts | 22nd April |
5. Writing | 17th June | |
6. Revision | final work | 28th July |
If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.
Make sure to check what type of costs the funding body will agree to cover. For each item, include:
To determine your budget, think about:
Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement.
Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.
I will compare …
A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.
Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.
A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.
A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.
A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.
All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.
Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.
Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.
If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.
McCombes, S. & George, T. (2023, June 13). How to Write a Research Proposal | Examples & Templates. Scribbr. Retrieved 2 July 2024, from https://www.scribbr.co.uk/the-research-process/research-proposal-explained/
Other students also liked, what is a research methodology | steps & tips, what is a literature review | guide, template, & examples, how to write a results section | tips & examples.
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Descriptive research.
2. direct comparisons of results, 3. large samples, 4. hypothesis testing, 1. superficiality, 2. narrow focus, 3. structural bias, 4. lack of context, 1. title page, 2. review of related literature, 3. research objectives and methodology, 4. data analysis, 5. ethical considerations, bibliography, and references, share this post on your network, you may also like these articles, title project proposal.
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(12 reviews)
Christine Davies, Carmarthen, Wales
Copyright Year: 2020
Last Update: 2021
Publisher: University of Wales Trinity Saint David
Language: English
Conditions of use.
Learn more about reviews.
Reviewed by Jennifer Taylor, Assistant Professor, Texas A&M University-Corpus Christi on 4/18/24
This resource is a quick guide to quantitative research in the social sciences and not a comprehensive resource. It provides a VERY general overview of quantitative research but offers a good starting place for students new to research. It... read more
Comprehensiveness rating: 4 see less
This resource is a quick guide to quantitative research in the social sciences and not a comprehensive resource. It provides a VERY general overview of quantitative research but offers a good starting place for students new to research. It offers links and references to additional resources that are more comprehensive in nature.
Content Accuracy rating: 4
The content is relatively accurate. The measurement scale section is very sparse. Not all types of research designs or statistical methods are included, but it is a guide, so details are meant to be limited.
Relevance/Longevity rating: 4
The examples were interesting and appropriate. The content is up to date and will be useful for several years.
Clarity rating: 5
The text was clearly written. Tables and figures are not referenced in the text, which would have been nice.
Consistency rating: 5
The framework is consistent across chapters with terminology clearly highlighted and defined.
Modularity rating: 5
The chapters are subdivided into section that can be divided and assigned as reading in a course. Most chapters are brief and concise, unless elaboration is necessary, such as with the data analysis chapter. Again, this is a guide and not a comprehensive text, so sections are shorter and don't always include every subtopic that may be considered.
Organization/Structure/Flow rating: 5
The guide is well organized. I appreciate that the topics are presented in a logical and clear manner. The topics are provided in an order consistent with traditional research methods.
Interface rating: 5
The interface was easy to use and navigate. The images were clear and easy to read.
Grammatical Errors rating: 5
I did not notice any grammatical errors.
Cultural Relevance rating: 5
The materials are not culturally insensitive or offensive in any way.
I teach a Marketing Research course to undergraduates. I would consider using some of the chapters or topics included, especially the overview of the research designs and the analysis of data section.
Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 3/9/24
The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers... read more
Comprehensiveness rating: 3 see less
The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers references to other resources that can be used to deepen the knowledge. The text does not include a glossary or index. The references in the figures for each chapter are not included in the reference section. It would be helpful to include those.
Overall, the text is accurate. For example, Figure 1 on page 6 provides a clear overview of the research process. It includes general definitions of primary and secondary research. It would be helpful to include more details to explain some of the examples before they are presented. For instance, the example on page 5 was unclear how it pertains to the literature review section.
In general, the text is relevant and up-to-date. The text includes many inferences of moving from qualitative to quantitative analysis. This was surprising to me as a quantitative researcher. The author mentions that moving from a qualitative to quantitative approach should only be done when needed. As a predominantly quantitative researcher, I would not advice those interested in transitioning to using a qualitative approach that qualitative research would enhance their research—not something that should only be done if you have to.
Clarity rating: 4
The text is written in a clear manner. It would be helpful to the reader if there was a description of the tables and figures in the text before they are presented.
Consistency rating: 4
The framework for each chapter and terminology used are consistent.
Modularity rating: 4
The text is clearly divided into sections within each chapter. Overall, the chapters are a similar brief length except for the chapter on data analysis, which is much more comprehensive than others.
Organization/Structure/Flow rating: 4
The topics in the text are presented in a clear and logical order. The order of the text follows the conventional research methodology in social sciences.
I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader.
Grammatical Errors rating: 3
There are some grammatical/typographical errors throughout. Of note, for Section 5 in the table of contents. “The” should be capitalized to start the title. In the title for Table 3, the “t” in typical should be capitalized.
Cultural Relevance rating: 4
The examples are culturally relevant. The text is geared towards learners in the UK, but examples are relevant for use in other countries (i.e., United States). I did not see any examples that may be considered culturally insensitive or offensive in any way.
I teach a course on research methods in a Bachelor of Science in Public Health program. I would consider using some of the text, particularly in the analysis chapter to supplement the current textbook in the future.
Reviewed by Finn Bell, Assistant Professor, University of Michigan, Dearborn on 1/3/24
For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary. read more
For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary.
Content Accuracy rating: 5
As far as I can tell, the text is accurate, error-free and unbiased.
Relevance/Longevity rating: 5
This text is up-to-date, and given the content, unlikely to become obsolete any time soon.
The text is very clear and accessible.
The text is internally consistent.
Given how short the text is, it seems unnecessary to divide it into smaller readings, nonetheless, it is clearly labelled such that an instructor could do so.
The text is well-organized and brings readers through basic quantitative methods in a logical, clear fashion.
Easy to navigate. Only one table that is split between pages, but not in a way that is confusing.
There were no noticeable grammatical errors.
The examples in this book don't give enough information to rate this effectively.
This text is truly a very quick guide at only 26 double-spaced pages. Nonetheless, Davies packs a lot of information on the basics of quantitative research methods into this text, in an engaging way with many examples of the concepts presented. This guide is more of a brief how-to that takes readers as far as how to select statistical tests. While it would be impossible to fully learn quantitative research from such a short text, of course, this resource provides a great introduction, overview, and refresher for program evaluation courses.
Reviewed by Shari Fedorowicz, Adjunct Professor, Bridgewater State University on 12/16/22
The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing... read more
Comprehensiveness rating: 5 see less
The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing the reader with the ability to distinguish two terms that frequently get confused. In addition, links and outside resources are provided to deepen the understanding as an option for the reader. The use of these links, coupled with diagrams and examples make this text comprehensive.
The content is mostly accurate. Given that it is a quick guide, the author chose a good selection of which types of research designs to include. However, some are not provided. For example, correlational or cross-correlational research is omitted and is not discussed in Section 3, but is used as a statistical example in the last section.
Examples utilized were appropriate and associated with terms adding value to the learning. The tables that included differentiation between types of statistical tests along with a parametric/nonparametric table were useful and relevant.
The purpose to the text and how to use this guide book is stated clearly and is established up front. The author is also very clear regarding the skill level of the user. Adding to the clarity are the tables with terms, definitions, and examples to help the reader unpack the concepts. The content related to the terms was succinct, direct, and clear. Many times examples or figures were used to supplement the narrative.
The text is consistent throughout from contents to references. Within each section of the text, the introductory paragraph under each section provides a clear understanding regarding what will be discussed in each section. The layout is consistent for each section and easy to follow.
The contents are visible and address each section of the text. A total of seven sections, including a reference section, is in the contents. Each section is outlined by what will be discussed in the contents. In addition, within each section, a heading is provided to direct the reader to the subtopic under each section.
The text is well-organized and segues appropriately. I would have liked to have seen an introductory section giving a narrative overview of what is in each section. This would provide the reader with the ability to get a preliminary glimpse into each upcoming sections and topics that are covered.
The book was easy to navigate and well-organized. Examples are presented in one color, links in another and last, figures and tables. The visuals supplemented the reading and placed appropriately. This provides an opportunity for the reader to unpack the reading by use of visuals and examples.
No significant grammatical errors.
The text is not offensive or culturally insensitive. Examples were inclusive of various races, ethnicities, and backgrounds.
This quick guide is a beneficial text to assist in unpacking the learning related to quantitative statistics. I would use this book to complement my instruction and lessons, or use this book as a main text with supplemental statistical problems and formulas. References to statistical programs were appropriate and were useful. The text did exactly what was stated up front in that it is a direct guide to quantitative statistics. It is well-written and to the point with content areas easy to locate by topic.
Reviewed by Sarah Capello, Assistant Professor, Radford University on 1/18/22
The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text. read more
The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text.
The content is mostly accurate. I would have preferred a few nuances to be hashed out a bit further to avoid potential reader confusion or misunderstanding of the concepts presented.
The content is current; however, some of the references cited in the text are outdated. Newer editions of those texts exist.
The text is very accessible and readable for a variety of audiences. Key terms are well-defined.
There are no content discrepancies within the text. The author even uses similarly shaped graphics for recurring purposes throughout the text (e.g., arrow call outs for further reading, rectangle call outs for examples).
The content is chunked nicely by topics and sections. If it were used for a course, it would be easy to assign different sections of the text for homework, etc. without confusing the reader if the instructor chose to present the content in a different order.
The author follows the structure of the research process. The organization of the text is easy to follow and comprehend.
All of the supplementary images (e.g., tables and figures) were beneficial to the reader and enhanced the text.
There are no significant grammatical errors.
I did not find any culturally offensive or insensitive references in the text.
This text does the difficult job of introducing the complicated concepts and processes of quantitative research in a quick and easy reference guide fairly well. I would not depend solely on this text to teach students about quantitative research, but it could be a good jumping off point for those who have no prior knowledge on this subject or those who need a gentle introduction before diving in to more advanced and complex readings of quantitative research methods.
Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 12/9/21
Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of... read more
Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of thought. There is no glossary but, for a guide of this length, a glossary does not seem like it would enhance the guide significantly.
The content is relatively accurate. Expanding the content a bit more or explaining that the methods and designs presented are not entirely inclusive would help. As there are different schools of thought regarding what should/should not be included in terms of these designs and methods, simply bringing attention to that and explaining a bit more would help.
Relevance/Longevity rating: 3
This content needs to be updated. Most of the sources cited are seven or more years old. Even more, it would be helpful to see more currently relevant examples. Some of the source authors such as Andy Field provide very interesting and dynamic instruction in general, but they have much more current information available.
The language used is clear and appropriate. Unnecessary jargon is not used. The intent is clear- to communicate simply in a straightforward manner.
The guide seems to be internally consistent in terms of terminology and framework. There do not seem to be issues in this area. Terminology is internally consistent.
For a guide of this length, the author structured this logically into sections. This guide could be adopted in whole or by section with limited modifications. Courses with fewer than seven modules could also logically group some of the sections.
This guide does present with logical organization. The topics presented are conceptually sequenced in a manner that helps learners build logically on prior conceptualization. This also provides a simple conceptual framework for instructors to guide learners through the process.
Interface rating: 4
The visuals themselves are simple, but they are clear and understandable without distracting the learner. The purpose is clear- that of learning rather than visuals for the sake of visuals. Likewise, navigation is clear and without issues beyond a broken link (the last source noted in the references).
This guide seems to be free of grammatical errors.
It would be interesting to see more cultural integration in a guide of this nature, but the guide is not culturally insensitive or offensive in any way. The language used seems to be consistent with APA's guidelines for unbiased language.
Reviewed by Heng Yu-Ku, Professor, University of Northern Colorado on 5/13/21
The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive... read more
The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive research study as an Appendix after section 7 (page 26) to help readers comprehend information better.
For the most part, the content is accurate and unbiased. However, the author only includes four types of research designs used on the social sciences that contain quantitative elements: 1. Mixed method, 2) Case study, 3) Quasi-experiment, and 3) Action research. I wonder why the correlational research is not included as another type of quantitative research design as it has been introduced and emphasized in section 6 by the author.
I believe the content is up-to-date and that necessary updates will be relatively easy and straightforward to implement.
The text is easy to read and provides adequate context for any technical terminology used. However, the author could provide more detailed information about estimating the minimum sample size but not just refer the readers to use the online sample calculators at a different website.
The text is internally consistent in terms of terminology and framework. The author provides the right amount of information with additional information or resources for the readers.
The text includes seven sections. Therefore, it is easier for the instructor to allocate or divide the content into different weeks of instruction within the course.
Yes, the topics in the text are presented in a logical and clear fashion. The author provides clear and precise terminologies, summarizes important content in Table or Figure forms, and offers examples in each section for readers to check their understanding.
The interface of the book is consistent and clear, and all the images and charts provided in the book are appropriate. However, I did encounter some navigation problems as a couple of links are not working or requires permission to access those (pages 10 and 27).
No grammatical errors were found.
No culturally incentive or offensive in its language and the examples provided were found.
As the book title stated, this book provides “A Quick Guide to Quantitative Research in Social Science. It offers easy-to-read information and introduces the readers to the research process, such as research questions, research paradigms, research process, research designs, research methods, data collection, data analysis, and data discussion. However, some links are not working or need permissions to access them (pages 10 and 27).
Reviewed by Hsiao-Chin Kuo, Assistant Professor, Northeastern Illinois University on 4/26/21, updated 4/28/21
As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and... read more
As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and process, discusses methods, data collection and analysis, and ends with writing a research report. It also identifies its target readers/users as those begins to explore quantitative research. It would be helpful to include more examples for readers/users who are new to quantitative research.
Its content is mostly accurate and no bias given its nature as a quick guide. Yet, it is also quite simplified, such as its explanations of mixed methods, case study, quasi-experimental research, and action research. It provides resources for extended reading, yet more recent works will be helpful.
The book is relevant given its nature as a quick guide. It would be helpful to provide more recent works in its resources for extended reading, such as the section for Survey Research (p. 12). It would also be helpful to include more information to introduce common tools and software for statistical analysis.
The book is written with clear and understandable language. Important terms and concepts are presented with plain explanations and examples. Figures and tables are also presented to support its clarity. For example, Table 4 (p. 20) gives an easy-to-follow overview of different statistical tests.
The framework is very consistent with key points, further explanations, examples, and resources for extended reading. The sample studies are presented following the layout of the content, such as research questions, design and methods, and analysis. These examples help reinforce readers' understanding of these common research elements.
The book is divided into seven chapters. Each chapter clearly discusses an aspect of quantitative research. It can be easily divided into modules for a class or for a theme in a research method class. Chapters are short and provides additional resources for extended reading.
The topics in the chapters are presented in a logical and clear structure. It is easy to follow to a degree. Though, it would be also helpful to include the chapter number and title in the header next to its page number.
The text is easy to navigate. Most of the figures and tables are displayed clearly. Yet, there are several sections with empty space that is a bit confusing in the beginning. Again, it can be helpful to include the chapter number/title next to its page number.
Grammatical Errors rating: 4
No major grammatical errors were found.
There are no cultural insensitivities noted.
Given the nature and purpose of this book, as a quick guide, it provides readers a quick reference for important concepts and terms related to quantitative research. Because this book is quite short (27 pages), it can be used as an overview/preview about quantitative research. Teacher's facilitation/input and extended readings will be needed for a deeper learning and discussion about aspects of quantitative research.
Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 1/6/21
It covers the most important topics such as research progress, resources, measurement, and analysis of the data. read more
It covers the most important topics such as research progress, resources, measurement, and analysis of the data.
The book accurately describes the types of research methods such as mixed-method, quasi-experiment, and case study. It talks about the research proposal and key differences between statistical analyses as well.
The book pinpointed the significance of running a quantitative research method and its relevance to the field of social science.
The book clearly tells us the differences between types of quantitative methods and the steps of running quantitative research for students.
The book is consistent in terms of terminologies such as research methods or types of statistical analysis.
It addresses the headlines and subheadlines very well and each subheading should be necessary for readers.
The book was organized very well to illustrate the topic of quantitative methods in the field of social science.
The pictures within the book could be further developed to describe the key concepts vividly.
The textbook contains no grammatical errors.
It is not culturally offensive in any way.
Overall, this is a simple and quick guide for this important topic. It should be valuable for undergraduate students who would like to learn more about research methods.
Reviewed by Pierre Lu, Associate Professor, University of Texas Rio Grande Valley on 11/20/20
As a quick guide to quantitative research in social sciences, the text covers most ideas and areas. read more
As a quick guide to quantitative research in social sciences, the text covers most ideas and areas.
Mostly accurate content.
As a quick guide, content is highly relevant.
Succinct and clear.
Internally, the text is consistent in terms of terminology used.
The text is easily and readily divisible into smaller sections that can be used as assignments.
I like that there are examples throughout the book.
Easy to read. No interface/ navigation problems.
No grammatical errors detected.
I am not aware of the culturally insensitive description. After all, this is a methodology book.
I think the book has potential to be adopted as a foundation for quantitative research courses, or as a review in the first weeks in advanced quantitative course.
Reviewed by Sarah Fischer, Assistant Professor, Marymount University on 7/31/20
It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable). read more
It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable).
Content Accuracy rating: 1
Contains VERY significant errors, such as saying that one can "accept" a hypothesis. (One of the key aspect of hypothesis testing is that one either rejects or fails to reject a hypothesis, but NEVER accepts a hypothesis.)
Very relevant to those experiencing the research process for the first time. However, it is written by someone working in the natural sciences but is a text for social sciences. This does not explain the errors, but does explain why sometimes the author assumes things about the readers ("hail from more subjectivist territory") that are likely not true.
Clarity rating: 3
Some statistical terminology not explained clearly (or accurately), although the author has made attempts to do both.
Very consistently laid out.
Chapters are very short yet also point readers to outside texts for additional information. Easy to follow.
Generally logically organized.
Easy to navigate, images clear. The additional sources included need to linked to.
Minor grammatical and usage errors throughout the text.
Makes efforts to be inclusive.
The idea of this book is strong--short guides like this are needed. However, this book would likely be strengthened by a revision to reduce inaccuracies and improve the definitions and technical explanations of statistical concepts. Since the book is specifically aimed at the social sciences, it would also improve the text to have more examples that are based in the social sciences (rather than the health sciences or the arts).
Reviewed by Michelle Page, Assistant Professor, Worcester State University on 5/30/20
This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new... read more
This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new researcher would not be able to use this as a stand alone guide for quantitative pursuits without having a supplemental text that explains the steps in the process more comprehensively. The introduction does provide this caveat.
Content Accuracy rating: 3
There are no biases or errors that could be distinguished; however, it’s simplicity in content, although accurate for an outline of process, may lack a conveyance of the deeper meanings behind the specific processes explained about qualitative research.
The content is outlined in traditional format to highlight quantitative considerations for formatting research foundational pieces. The resources/references used to point the reader to literature sources can be easily updated with future editions.
The jargon in the text is simple to follow and provides adequate context for its purpose. It is simplified for its intention as a guide which is appropriate.
Each section of the text follows a consistent flow. Explanation of the research content or concept is defined and then a connection to literature is provided to expand the readers understanding of the section’s content. Terminology is consistent with the qualitative process.
As an “outline” and guide, this text can be used to quickly identify the critical parts of the quantitative process. Although each section does not provide deeper content for meaningful use as a stand alone text, it’s utility would be excellent as a reference for a course and can be used as an content guide for specific research courses.
The text’s outline and content are aligned and are in a logical flow in terms of the research considerations for quantitative research.
The only issue that the format was not able to provide was linkable articles. These would have to be cut and pasted into a browser. Functional clickable links in a text are very successful at leading the reader to the supplemental material.
No grammatical errors were noted.
This is a very good outline “guide” to help a new or student researcher to demystify the quantitative process. A successful outline of any process helps to guide work in a logical and systematic way. I think this simple guide is a great adjunct to more substantial research context.
About the book.
This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real help.
The booklet was amended in 2022 to take into account previous review comments.
Christine Davies , Ph.D
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Methodology
Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.
Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.
Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).
Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.
Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.
You can use quantitative research methods for descriptive, correlational or experimental research.
Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.
To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).
Research method | How to use | Example |
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Control or manipulate an to measure its effect on a dependent variable. | To test whether an intervention can reduce procrastination in college students, you give equal-sized groups either a procrastination intervention or a comparable task. You compare self-ratings of procrastination behaviors between the groups after the intervention. | |
Ask questions of a group of people in-person, over-the-phone or online. | You distribute with rating scales to first-year international college students to investigate their experiences of culture shock. | |
(Systematic) observation | Identify a behavior or occurrence of interest and monitor it in its natural setting. | To study college classroom participation, you sit in on classes to observe them, counting and recording the prevalence of active and passive behaviors by students from different backgrounds. |
Secondary research | Collect data that has been gathered for other purposes e.g., national surveys or historical records. | To assess whether attitudes towards climate change have changed since the 1980s, you collect relevant questionnaire data from widely available . |
Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.
Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .
Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.
Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .
First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.
You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.
Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:
Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.
The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.
Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.
Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.
Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:
Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.
Predetermined variables and measurement procedures can mean that you ignore other relevant observations.
Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.
Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.
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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
Research bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
Operationalization means turning abstract conceptual ideas into measurable observations.
For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.
Reliability and validity are both about how well a method measures something:
If you are doing experimental research, you also have to consider the internal and external validity of your experiment.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.
Bhandari, P. (2023, June 22). What Is Quantitative Research? | Definition, Uses & Methods. Scribbr. Retrieved July 2, 2024, from https://www.scribbr.com/methodology/quantitative-research/
Other students also liked, descriptive statistics | definitions, types, examples, inferential statistics | an easy introduction & examples, what is your plagiarism score.
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Department of Anaesthesiology, Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India
Writing the proposal of a research work in the present era is a challenging task due to the constantly evolving trends in the qualitative research design and the need to incorporate medical advances into the methodology. The proposal is a detailed plan or ‘blueprint’ for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of the proposals at post-graduate evaluation committees and application proposals for funding are substandard. A search was conducted with keywords such as research proposal, writing proposal and qualitative using search engines, namely, PubMed and Google Scholar, and an attempt has been made to provide broad guidelines for writing a scientifically appropriate research proposal.
A clean, well-thought-out proposal forms the backbone for the research itself and hence becomes the most important step in the process of conduct of research.[ 1 ] The objective of preparing a research proposal would be to obtain approvals from various committees including ethics committee [details under ‘Research methodology II’ section [ Table 1 ] in this issue of IJA) and to request for grants. However, there are very few universally accepted guidelines for preparation of a good quality research proposal. A search was performed with keywords such as research proposal, funding, qualitative and writing proposals using search engines, namely, PubMed, Google Scholar and Scopus.
Five ‘C’s while writing a literature review
A proposal needs to show how your work fits into what is already known about the topic and what new paradigm will it add to the literature, while specifying the question that the research will answer, establishing its significance, and the implications of the answer.[ 2 ] The proposal must be capable of convincing the evaluation committee about the credibility, achievability, practicality and reproducibility (repeatability) of the research design.[ 3 ] Four categories of audience with different expectations may be present in the evaluation committees, namely academic colleagues, policy-makers, practitioners and lay audiences who evaluate the research proposal. Tips for preparation of a good research proposal include; ‘be practical, be persuasive, make broader links, aim for crystal clarity and plan before you write’. A researcher must be balanced, with a realistic understanding of what can be achieved. Being persuasive implies that researcher must be able to convince other researchers, research funding agencies, educational institutions and supervisors that the research is worth getting approval. The aim of the researcher should be clearly stated in simple language that describes the research in a way that non-specialists can comprehend, without use of jargons. The proposal must not only demonstrate that it is based on an intelligent understanding of the existing literature but also show that the writer has thought about the time needed to conduct each stage of the research.[ 4 , 5 ]
The contents or formats of a research proposal vary depending on the requirements of evaluation committee and are generally provided by the evaluation committee or the institution.
In general, a cover page should contain the (i) title of the proposal, (ii) name and affiliation of the researcher (principal investigator) and co-investigators, (iii) institutional affiliation (degree of the investigator and the name of institution where the study will be performed), details of contact such as phone numbers, E-mail id's and lines for signatures of investigators.
The main contents of the proposal may be presented under the following headings: (i) introduction, (ii) review of literature, (iii) aims and objectives, (iv) research design and methods, (v) ethical considerations, (vi) budget, (vii) appendices and (viii) citations.[ 4 ]
It is also sometimes termed as ‘need for study’ or ‘abstract’. Introduction is an initial pitch of an idea; it sets the scene and puts the research in context.[ 6 ] The introduction should be designed to create interest in the reader about the topic and proposal. It should convey to the reader, what you want to do, what necessitates the study and your passion for the topic.[ 7 ] Some questions that can be used to assess the significance of the study are: (i) Who has an interest in the domain of inquiry? (ii) What do we already know about the topic? (iii) What has not been answered adequately in previous research and practice? (iv) How will this research add to knowledge, practice and policy in this area? Some of the evaluation committees, expect the last two questions, elaborated under a separate heading of ‘background and significance’.[ 8 ] Introduction should also contain the hypothesis behind the research design. If hypothesis cannot be constructed, the line of inquiry to be used in the research must be indicated.
It refers to all sources of scientific evidence pertaining to the topic in interest. In the present era of digitalisation and easy accessibility, there is an enormous amount of relevant data available, making it a challenge for the researcher to include all of it in his/her review.[ 9 ] It is crucial to structure this section intelligently so that the reader can grasp the argument related to your study in relation to that of other researchers, while still demonstrating to your readers that your work is original and innovative. It is preferable to summarise each article in a paragraph, highlighting the details pertinent to the topic of interest. The progression of review can move from the more general to the more focused studies, or a historical progression can be used to develop the story, without making it exhaustive.[ 1 ] Literature should include supporting data, disagreements and controversies. Five ‘C's may be kept in mind while writing a literature review[ 10 ] [ Table 1 ].
The research purpose (or goal or aim) gives a broad indication of what the researcher wishes to achieve in the research. The hypothesis to be tested can be the aim of the study. The objectives related to parameters or tools used to achieve the aim are generally categorised as primary and secondary objectives.
The objective here is to convince the reader that the overall research design and methods of analysis will correctly address the research problem and to impress upon the reader that the methodology/sources chosen are appropriate for the specific topic. It should be unmistakably tied to the specific aims of your study.
In this section, the methods and sources used to conduct the research must be discussed, including specific references to sites, databases, key texts or authors that will be indispensable to the project. There should be specific mention about the methodological approaches to be undertaken to gather information, about the techniques to be used to analyse it and about the tests of external validity to which researcher is committed.[ 10 , 11 ]
The components of this section include the following:[ 4 ]
Population refers to all the elements (individuals, objects or substances) that meet certain criteria for inclusion in a given universe,[ 12 ] and sample refers to subset of population which meets the inclusion criteria for enrolment into the study. The inclusion and exclusion criteria should be clearly defined. The details pertaining to sample size are discussed in the article “Sample size calculation: Basic priniciples” published in this issue of IJA.
The researcher is expected to give a detailed account of the methodology adopted for collection of data, which include the time frame required for the research. The methodology should be tested for its validity and ensure that, in pursuit of achieving the results, the participant's life is not jeopardised. The author should anticipate and acknowledge any potential barrier and pitfall in carrying out the research design and explain plans to address them, thereby avoiding lacunae due to incomplete data collection. If the researcher is planning to acquire data through interviews or questionnaires, copy of the questions used for the same should be attached as an annexure with the proposal.
This addresses the strength of the research with respect to its neutrality, consistency and applicability. Rigor must be reflected throughout the proposal.
It refers to the robustness of a research method against bias. The author should convey the measures taken to avoid bias, viz. blinding and randomisation, in an elaborate way, thus ensuring that the result obtained from the adopted method is purely as chance and not influenced by other confounding variables.
Consistency considers whether the findings will be consistent if the inquiry was replicated with the same participants and in a similar context. This can be achieved by adopting standard and universally accepted methods and scales.
Applicability refers to the degree to which the findings can be applied to different contexts and groups.[ 13 ]
This section deals with the reduction and reconstruction of data and its analysis including sample size calculation. The researcher is expected to explain the steps adopted for coding and sorting the data obtained. Various tests to be used to analyse the data for its robustness, significance should be clearly stated. Author should also mention the names of statistician and suitable software which will be used in due course of data analysis and their contribution to data analysis and sample calculation.[ 9 ]
Medical research introduces special moral and ethical problems that are not usually encountered by other researchers during data collection, and hence, the researcher should take special care in ensuring that ethical standards are met. Ethical considerations refer to the protection of the participants' rights (right to self-determination, right to privacy, right to autonomy and confidentiality, right to fair treatment and right to protection from discomfort and harm), obtaining informed consent and the institutional review process (ethical approval). The researcher needs to provide adequate information on each of these aspects.
Informed consent needs to be obtained from the participants (details discussed in further chapters), as well as the research site and the relevant authorities.
When the researcher prepares a research budget, he/she should predict and cost all aspects of the research and then add an additional allowance for unpredictable disasters, delays and rising costs. All items in the budget should be justified.
Appendices are documents that support the proposal and application. The appendices will be specific for each proposal but documents that are usually required include informed consent form, supporting documents, questionnaires, measurement tools and patient information of the study in layman's language.
As with any scholarly research paper, you must cite the sources you used in composing your proposal. Although the words ‘references and bibliography’ are different, they are used interchangeably. It refers to all references cited in the research proposal.
Successful, qualitative research proposals should communicate the researcher's knowledge of the field and method and convey the emergent nature of the qualitative design. The proposal should follow a discernible logic from the introduction to presentation of the appendices.
Conflicts of interest.
There are no conflicts of interest.
Advice and guidance on writing a proposal for a student research project.
A research proposal should describe what you will investigate, why it is important to the discipline and how you will conduct your research.
Simply put, it is your plan for the research you intend to conduct. All research proposals are designed to persuade someone about how and why your intended project is worthwhile.
In your proposal you will need to explain and defend your choices. Always think about the exact reasons why you are making specific choices and why they are the best options available to you and your project.
Your research proposal aims should be centred on:
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Our Research Writing workshop will look at some of the main writing challenges associated with writing a large-scale research project and look at strategies to manage your writing on a day-to-day basis. It will identify ways to plan, organise and map out the structure of your writing to allow you to develop an effective writing schedule and make continuous progress on your dissertation project.
The format of a research proposal varies between fields and levels of study but most proposals should contain at least these elements: introduction, literature review, research design and reference list.
Generally, research proposals can range from 500-1500 words or one to a few pages long. Typically, proposals for larger projects such as a PhD dissertation or funding requests, are longer and much more detailed.
Remember, the goal of your research proposal is to outline clearly and concisely exactly what your research will entail and accomplish, how it will do so and why it is important. If you are writing to a strictly enforced word count, a research proposal can be a great test of your ability to express yourself concisely!
The first part of your proposal is the initial pitch for your project, so make sure it succinctly explains what you want to do and why. In other words, this is where you answer the reader’s “so what?” It should typically include: introducing the topic , outlining your problem statement and research question(s) and giving background and context. Some important questions to shape your introduction include:
If your proposal is very long, you might include separate sections with more detailed information on the background and context, problem statement, aims and objectives, and importance of the research.
It’s important to show that you’re familiar with the most important research on your topic. A strong literature review convinces the reader that your project has a solid foundation in existing knowledge or theory (i.e. how it relates to established research in the field).
Your literature review will also show that you’re not simply repeating what other people have already done or said. This is also where you explain why your research is necessary. You might want to consider some of the following prompts:
Following the literature review, it is a good idea to restate your main objectives, bringing the focus back to your own project. The research design/ methodology section should describe the overall approach and practical steps you will take to answer your research questions. You also need to demonstrate the feasibility of the project keeping in mind time and other constraints.
You should definitely include:
Make sure you are not simply compiling a list of methods. Instead, aim to make an argument for why this is the most appropriate, valid and reliable way to approach answering your question. Remember you should always be defending your choices!
To ensure you finish your proposal on a strong note, it is a good idea to explore and/or emphasise the potential implications of the research. This means: what do you intend to contribute to existing knowledge on the topic?
Although you cannot know the results of your research until you have actually done the work, you should be going into the project with a clear idea of how your work will contribute to your field. This section might even be considered the most critical to your research proposal’s argument because it expresses exactly why your research is necessary.
You should consider covering at least some of the following topics:
This part is not about stating the specific results that you expect to obtain but rather, this is the section where you explicitly state how your findings will be valuable.
This section is where you want to wrap it all up in a nice pretty bow. It is just like the concluding paragraph that you would structure and craft for a typical essay, see our essay planning template for guidance. You should briefly summarise your research proposal and reinforce your research purpose.
Your research proposal MUST include proper citations for every source you have used and full references. Please consult your departmental referencing styles to ensure you are citing and referencing in an appropriate way.
Try and avoid these common pitfalls when you are writing your research proposal:
You might also need to include a schedule and/or a budget depending on your requirements. Some tools to help include:
For guidance regarding specific research proposals (including templates), please check with your specific departments.
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A Sample Quantitative Research Proposal Written in the APA 6th Style. [Note: This sample proposal is based on a composite of past proposals, simulated information and references, and material I've included for illustration purposes - it is based roughly on a fairly standard research proposal; I say roughly because there is no one set way of ...
NOTE: This proposal is included in the ancillary materials of Research Design with permission of the author. Hayes, M. M. (2007). Design and analysis of the student strengths index (SSI) for nontraditional graduate students. Unpublished master's thesis. University of Nebraska, Lincoln, NE. with the task of deciding who to admit into graduate ...
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".
The investigator specifies the maximum discrepancy between the sample and population proportion of ± 5%. To determine the sample size, the investigator would use the formula. n = (z/p)2π(1-π), n = the required sample size. p = the desired maximum discrepancy (i.e. ± 5%) π = the population proportion.
This chapter provides a comprehensive guideline for writing a research proposal in quantitative approach. It starts with the definition and purpose of writing a research proposal followed by a description of essential parts of a research proposal and subjects included in each part, organization of a research proposal, and guidelines for writing different parts of a research proposal including ...
1. Introduce the overall methodological approach. 2. Indicate how the approach fits the overall research design. 3. Describe the specific methods of data collection. 4. Explain how you intend to ...
Well-written proposals offer clear and appropriate alignments from the guiding research question(s) through the study design, data, sample, analysis, and its implications. Quantitative research—and proposals—typically involve one or more of three types of questions: descriptive, explanatory, and predictive. Descriptive questions
Make sure you can ask the critical what, who, and how questions of your research before you put pen to paper. Your research proposal should include (at least) 5 essential components : Title - provides the first taste of your research, in broad terms. Introduction - explains what you'll be researching in more detail.
Sample research proposals written by doctoral students in each of the key areas covered in Research Design--quantitative, qualitative, and mixed methods—are provided as a useful reference. A Research Proposal checklist also serves to help guide your own proposal-writing.› Morales Proposal_Qualitative Study› Kottich Proposal_Quantitative Study
Designing Research Proposal in Quantitative Approach. October 2022. DOI: 10.1007/978-981-19-5441-2_10. In book: Principles of Social Research Methodology (pp.131-156) Authors: Md. Rezaul Karim ...
As you write up your research proposal, remember the all-important core purpose: to convince. Your research proposal needs to sell your study in terms of suitability and viability. So, focus on crafting a convincing narrative to ensure a strong proposal. At the same time, pay close attention to your university's requirements.
The basic procedure of a quantitative design is: 1. Make your observations about something that is unknown, unexplained, or new. Investigate current theory surrounding your problem or issue. 2. Hypothesize an explanation for those observations. 3. Make a prediction of outcomes based on your hypotheses.
This research will utilize a mixed-methods approach to gather both quantitative and qualitative data. The study will include the following components: 3.2 Participants. ... This research proposal aims to investigate the impact of online education on student learning outcomes through a comparative study with traditional face-to-face instruction ...
A Guide to Quantitative Research Proposals. Resources. In this essay, noted scholar Elizabeth Tipton elaborates on how to best articulate quantitative research design in grant proposals. This essay is a companion piece to our "A Guide to Writing Successful Field Initiated Research Grant Proposals," which provides general information about ...
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'.
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
A quantitative approach is the most used research framework. It is a set of tactics, methodologies, and assumptions that are used to investigate psychological, social, and economic processes using quantitative patterns. The type of study design utilized in studies is not usually stated explicitly. There is a lot of research proposal templates that may help you in making a comprehensive ...
The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive research study as an Appendix after section 7 (page 26) to help readers comprehend information better.
Quantitative research methods. You can use quantitative research methods for descriptive, correlational or experimental research. In descriptive research, you simply seek an overall summary of your study variables.; In correlational research, you investigate relationships between your study variables.; In experimental research, you systematically examine whether there is a cause-and-effect ...
It puts the proposal in context. 3. The introduction typically begins with a statement of the research problem in precise and clear terms. 1. The importance of the statement of the research problem 5: The statement of the problem is the essential basis for the construction of a research proposal (research objectives, hypotheses, methodology ...
A proposal needs to show how your work fits into what is already known about the topic and what new paradigm will it add to the literature, while specifying the question that the research will answer, establishing its significance, and the implications of the answer. [ 2] The proposal must be capable of convincing the evaluation committee about ...
The format of a research proposal varies between fields and levels of study but most proposals should contain at least these elements: introduction, literature review, research design and reference list. Generally, research proposals can range from 500-1500 words or one to a few pages long. Typically, proposals for larger projects such as a PhD ...
A research proposal is like a roadmap for a study, outlining its purpose, methods, and expected outcomes. Typically, it consists of several key sections.