• Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • QuestionPro

survey software icon

  • Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
  • Resources Blog eBooks Survey Templates Case Studies Training Help center

how to make data analysis in research proposal

Home Market Research

Data Analysis in Research: Types & Methods

data-analysis-in-research

Content Index

Why analyze data in research?

Types of data in research, finding patterns in the qualitative data, methods used for data analysis in qualitative research, preparing data for analysis, methods used for data analysis in quantitative research, considerations in research data analysis, what is data analysis in research.

Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. 

Three essential things occur during the data analysis process — the first is data organization . Summarization and categorization together contribute to becoming the second known method used for data reduction. It helps find patterns and themes in the data for easy identification and linking. The third and last way is data analysis – researchers do it in both top-down and bottom-up fashion.

LEARN ABOUT: Research Process Steps

On the other hand, Marshall and Rossman describe data analysis as a messy, ambiguous, and time-consuming but creative and fascinating process through which a mass of collected data is brought to order, structure and meaning.

We can say that “the data analysis and data interpretation is a process representing the application of deductive and inductive logic to the research and data analysis.”

Researchers rely heavily on data as they have a story to tell or research problems to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem – we call it ‘Data Mining’, which often reveals some interesting patterns within the data that are worth exploring.

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased toward unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research. 

Create a Free Account

Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.

  • Qualitative data: When the data presented has words and descriptions, then we call it qualitative data . Although you can observe this data, it is subjective and harder to analyze data in research, especially for comparison. Example: Quality data represents everything describing taste, experience, texture, or an opinion that is considered quality data. This type of data is usually collected through focus groups, personal qualitative interviews , qualitative observation or using open-ended questions in surveys.
  • Quantitative data: Any data expressed in numbers of numerical figures are called quantitative data . This type of data can be distinguished into categories, grouped, measured, calculated, or ranked. Example: questions such as age, rank, cost, length, weight, scores, etc. everything comes under this type of data. You can present such data in graphical format, charts, or apply statistical analysis methods to this data. The (Outcomes Measurement Systems) OMS questionnaires in surveys are a significant source of collecting numeric data.
  • Categorical data: It is data presented in groups. However, an item included in the categorical data cannot belong to more than one group. Example: A person responding to a survey by telling his living style, marital status, smoking habit, or drinking habit comes under the categorical data. A chi-square test is a standard method used to analyze this data.

Learn More : Examples of Qualitative Data in Education

Data analysis in qualitative research

Data analysis and qualitative data research work a little differently from the numerical data as the quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting insight from such complicated information is a complicated process. Hence it is typically used for exploratory research and data analysis .

Although there are several ways to find patterns in the textual information, a word-based method is the most relied and widely used global technique for research and data analysis. Notably, the data analysis process in qualitative research is manual. Here the researchers usually read the available data and find repetitive or commonly used words. 

For example, while studying data collected from African countries to understand the most pressing issues people face, researchers might find  “food”  and  “hunger” are the most commonly used words and will highlight them for further analysis.

LEARN ABOUT: Level of Analysis

The keyword context is another widely used word-based technique. In this method, the researcher tries to understand the concept by analyzing the context in which the participants use a particular keyword.  

For example , researchers conducting research and data analysis for studying the concept of ‘diabetes’ amongst respondents might analyze the context of when and how the respondent has used or referred to the word ‘diabetes.’

The scrutiny-based technique is also one of the highly recommended  text analysis  methods used to identify a quality data pattern. Compare and contrast is the widely used method under this technique to differentiate how a specific text is similar or different from each other. 

For example: To find out the “importance of resident doctor in a company,” the collected data is divided into people who think it is necessary to hire a resident doctor and those who think it is unnecessary. Compare and contrast is the best method that can be used to analyze the polls having single-answer questions types .

Metaphors can be used to reduce the data pile and find patterns in it so that it becomes easier to connect data with theory.

Variable Partitioning is another technique used to split variables so that researchers can find more coherent descriptions and explanations from the enormous data.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

There are several techniques to analyze the data in qualitative research, but here are some commonly used methods,

  • Content Analysis:  It is widely accepted and the most frequently employed technique for data analysis in research methodology. It can be used to analyze the documented information from text, images, and sometimes from the physical items. It depends on the research questions to predict when and where to use this method.
  • Narrative Analysis: This method is used to analyze content gathered from various sources such as personal interviews, field observation, and  surveys . The majority of times, stories, or opinions shared by people are focused on finding answers to the research questions.
  • Discourse Analysis:  Similar to narrative analysis, discourse analysis is used to analyze the interactions with people. Nevertheless, this particular method considers the social context under which or within which the communication between the researcher and respondent takes place. In addition to that, discourse analysis also focuses on the lifestyle and day-to-day environment while deriving any conclusion.
  • Grounded Theory:  When you want to explain why a particular phenomenon happened, then using grounded theory for analyzing quality data is the best resort. Grounded theory is applied to study data about the host of similar cases occurring in different settings. When researchers are using this method, they might alter explanations or produce new ones until they arrive at some conclusion.

LEARN ABOUT: 12 Best Tools for Researchers

Data analysis in quantitative research

The first stage in research and data analysis is to make it for the analysis so that the nominal data can be converted into something meaningful. Data preparation consists of the below phases.

Phase I: Data Validation

Data validation is done to understand if the collected data sample is per the pre-set standards, or it is a biased data sample again divided into four different stages

  • Fraud: To ensure an actual human being records each response to the survey or the questionnaire
  • Screening: To make sure each participant or respondent is selected or chosen in compliance with the research criteria
  • Procedure: To ensure ethical standards were maintained while collecting the data sample
  • Completeness: To ensure that the respondent has answered all the questions in an online survey. Else, the interviewer had asked all the questions devised in the questionnaire.

Phase II: Data Editing

More often, an extensive research data sample comes loaded with errors. Respondents sometimes fill in some fields incorrectly or sometimes skip them accidentally. Data editing is a process wherein the researchers have to confirm that the provided data is free of such errors. They need to conduct necessary checks and outlier checks to edit the raw edit and make it ready for analysis.

Phase III: Data Coding

Out of all three, this is the most critical phase of data preparation associated with grouping and assigning values to the survey responses . If a survey is completed with a 1000 sample size, the researcher will create an age bracket to distinguish the respondents based on their age. Thus, it becomes easier to analyze small data buckets rather than deal with the massive data pile.

LEARN ABOUT: Steps in Qualitative Research

After the data is prepared for analysis, researchers are open to using different research and data analysis methods to derive meaningful insights. For sure, statistical analysis plans are the most favored to analyze numerical data. In statistical analysis, distinguishing between categorical data and numerical data is essential, as categorical data involves distinct categories or labels, while numerical data consists of measurable quantities. The method is again classified into two groups. First, ‘Descriptive Statistics’ used to describe data. Second, ‘Inferential statistics’ that helps in comparing the data .

Descriptive statistics

This method is used to describe the basic features of versatile types of data in research. It presents the data in such a meaningful way that pattern in the data starts making sense. Nevertheless, the descriptive analysis does not go beyond making conclusions. The conclusions are again based on the hypothesis researchers have formulated so far. Here are a few major types of descriptive analysis methods.

Measures of Frequency

  • Count, Percent, Frequency
  • It is used to denote home often a particular event occurs.
  • Researchers use it when they want to showcase how often a response is given.

Measures of Central Tendency

  • Mean, Median, Mode
  • The method is widely used to demonstrate distribution by various points.
  • Researchers use this method when they want to showcase the most commonly or averagely indicated response.

Measures of Dispersion or Variation

  • Range, Variance, Standard deviation
  • Here the field equals high/low points.
  • Variance standard deviation = difference between the observed score and mean
  • It is used to identify the spread of scores by stating intervals.
  • Researchers use this method to showcase data spread out. It helps them identify the depth until which the data is spread out that it directly affects the mean.

Measures of Position

  • Percentile ranks, Quartile ranks
  • It relies on standardized scores helping researchers to identify the relationship between different scores.
  • It is often used when researchers want to compare scores with the average count.

For quantitative research use of descriptive analysis often give absolute numbers, but the in-depth analysis is never sufficient to demonstrate the rationale behind those numbers. Nevertheless, it is necessary to think of the best method for research and data analysis suiting your survey questionnaire and what story researchers want to tell. For example, the mean is the best way to demonstrate the students’ average scores in schools. It is better to rely on the descriptive statistics when the researchers intend to keep the research or outcome limited to the provided  sample  without generalizing it. For example, when you want to compare average voting done in two different cities, differential statistics are enough.

Descriptive analysis is also called a ‘univariate analysis’ since it is commonly used to analyze a single variable.

Inferential statistics

Inferential statistics are used to make predictions about a larger population after research and data analysis of the representing population’s collected sample. For example, you can ask some odd 100 audiences at a movie theater if they like the movie they are watching. Researchers then use inferential statistics on the collected  sample  to reason that about 80-90% of people like the movie. 

Here are two significant areas of inferential statistics.

  • Estimating parameters: It takes statistics from the sample research data and demonstrates something about the population parameter.
  • Hypothesis test: I t’s about sampling research data to answer the survey research questions. For example, researchers might be interested to understand if the new shade of lipstick recently launched is good or not, or if the multivitamin capsules help children to perform better at games.

These are sophisticated analysis methods used to showcase the relationship between different variables instead of describing a single variable. It is often used when researchers want something beyond absolute numbers to understand the relationship between variables.

Here are some of the commonly used methods for data analysis in research.

  • Correlation: When researchers are not conducting experimental research or quasi-experimental research wherein the researchers are interested to understand the relationship between two or more variables, they opt for correlational research methods.
  • Cross-tabulation: Also called contingency tables,  cross-tabulation  is used to analyze the relationship between multiple variables.  Suppose provided data has age and gender categories presented in rows and columns. A two-dimensional cross-tabulation helps for seamless data analysis and research by showing the number of males and females in each age category.
  • Regression analysis: For understanding the strong relationship between two variables, researchers do not look beyond the primary and commonly used regression analysis method, which is also a type of predictive analysis used. In this method, you have an essential factor called the dependent variable. You also have multiple independent variables in regression analysis. You undertake efforts to find out the impact of independent variables on the dependent variable. The values of both independent and dependent variables are assumed as being ascertained in an error-free random manner.
  • Frequency tables: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
  • Analysis of variance: The statistical procedure is used for testing the degree to which two or more vary or differ in an experiment. A considerable degree of variation means research findings were significant. In many contexts, ANOVA testing and variance analysis are similar.
  • Researchers must have the necessary research skills to analyze and manipulation the data , Getting trained to demonstrate a high standard of research practice. Ideally, researchers must possess more than a basic understanding of the rationale of selecting one statistical method over the other to obtain better data insights.
  • Usually, research and data analytics projects differ by scientific discipline; therefore, getting statistical advice at the beginning of analysis helps design a survey questionnaire, select data collection methods , and choose samples.

LEARN ABOUT: Best Data Collection Tools

  • The primary aim of data research and analysis is to derive ultimate insights that are unbiased. Any mistake in or keeping a biased mind to collect data, selecting an analysis method, or choosing  audience  sample il to draw a biased inference.
  • Irrelevant to the sophistication used in research data and analysis is enough to rectify the poorly defined objective outcome measurements. It does not matter if the design is at fault or intentions are not clear, but lack of clarity might mislead readers, so avoid the practice.
  • The motive behind data analysis in research is to present accurate and reliable data. As far as possible, avoid statistical errors, and find a way to deal with everyday challenges like outliers, missing data, data altering, data mining , or developing graphical representation.

LEARN MORE: Descriptive Research vs Correlational Research The sheer amount of data generated daily is frightening. Especially when data analysis has taken center stage. in 2018. In last year, the total data supply amounted to 2.8 trillion gigabytes. Hence, it is clear that the enterprises willing to survive in the hypercompetitive world must possess an excellent capability to analyze complex research data, derive actionable insights, and adapt to the new market needs.

LEARN ABOUT: Average Order Value

QuestionPro is an online survey platform that empowers organizations in data analysis and research and provides them a medium to collect data by creating appealing surveys.

MORE LIKE THIS

employee engagement software

Top 20 Employee Engagement Software Solutions

May 3, 2024

customer experience software

15 Best Customer Experience Software of 2024

May 2, 2024

Journey Orchestration Platforms

Journey Orchestration Platforms: Top 11 Platforms in 2024

employee pulse survey tools

Top 12 Employee Pulse Survey Tools Unlocking Insights in 2024

May 1, 2024

Other categories

  • Academic Research
  • Artificial Intelligence
  • Assessments
  • Brand Awareness
  • Case Studies
  • Communities
  • Consumer Insights
  • Customer effort score
  • Customer Engagement
  • Customer Experience
  • Customer Loyalty
  • Customer Research
  • Customer Satisfaction
  • Employee Benefits
  • Employee Engagement
  • Employee Retention
  • Friday Five
  • General Data Protection Regulation
  • Insights Hub
  • Life@QuestionPro
  • Market Research
  • Mobile diaries
  • Mobile Surveys
  • New Features
  • Online Communities
  • Question Types
  • Questionnaire
  • QuestionPro Products
  • Release Notes
  • Research Tools and Apps
  • Revenue at Risk
  • Survey Templates
  • Training Tips
  • Uncategorized
  • Video Learning Series
  • What’s Coming Up
  • Workforce Intelligence

Banner

  • RIT Libraries
  • Data Analytics Resources
  • Writing a Research Proposal
  • Electronic Books
  • Print Books
  • Data Science: Journals
  • More Journals, Websites
  • Alerts, IDS Express
  • Readings on Data
  • Sources with Data
  • Google Scholar Library Links
  • Zotero-Citation Management Tool
  • Writing a Literature Review
  • ProQuest Research Companion
  • Thesis Submission Instructions
  • Associations

Writing a Rsearch Proposal

A  research proposal  describes what you will investigate, why it’s important, and how you will conduct your research.  Your paper should include the topic, research question and hypothesis, methods, predictions, and results (if not actual, then projected).

Research Proposal Aims

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.

Facebook icon

Help is Available

how to make data analysis in research proposal

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

CRENC Learn

How to Create a Data Analysis Plan: A Detailed Guide

by Barche Blaise | Aug 12, 2020 | Writing

how to create a data analysis plan

If a good research question equates to a story then, a roadmap will be very vita l for good storytelling. We advise every student/researcher to personally write his/her data analysis plan before seeking any advice. In this blog article, we will explore how to create a data analysis plan: the content and structure.

This data analysis plan serves as a roadmap to how data collected will be organised and analysed. It includes the following aspects:

  • Clearly states the research objectives and hypothesis
  • Identifies the dataset to be used
  • Inclusion and exclusion criteria
  • Clearly states the research variables
  • States statistical test hypotheses and the software for statistical analysis
  • Creating shell tables

1. Stating research question(s), objectives and hypotheses:

All research objectives or goals must be clearly stated. They must be Specific, Measurable, Attainable, Realistic and Time-bound (SMART). Hypotheses are theories obtained from personal experience or previous literature and they lay a foundation for the statistical methods that will be applied to extrapolate results to the entire population.

2. The dataset:

The dataset that will be used for statistical analysis must be described and important aspects of the dataset outlined. These include; owner of the dataset, how to get access to the dataset, how the dataset was checked for quality control and in what program is the dataset stored (Excel, Epi Info, SQL, Microsoft access etc.).

3. The inclusion and exclusion criteria :

They guide the aspects of the dataset that will be used for data analysis. These criteria will also guide the choice of variables included in the main analysis.

4. Variables:

Every variable collected in the study should be clearly stated. They should be presented based on the level of measurement (ordinal/nominal or ratio/interval levels), or the role the variable plays in the study (independent/predictors or dependent/outcome variables). The variable types should also be outlined.  The variable type in conjunction with the research hypothesis forms the basis for selecting the appropriate statistical tests for inferential statistics. A good data analysis plan should summarize the variables as demonstrated in Figure 1 below.

Presentation of variables in a data analysis plan

5. Statistical software

There are tons of software packages for data analysis, some common examples are SPSS, Epi Info, SAS, STATA, Microsoft Excel. Include the version number,  year of release and author/manufacturer. Beginners have the tendency to try different software and finally not master any. It is rather good to select one and master it because almost all statistical software have the same performance for basic and the majority of advance analysis needed for a student thesis. This is what we recommend to all our students at CRENC before they begin writing their results section .

6. Selecting the appropriate statistical method to test hypotheses

Depending on the research question, hypothesis and type of variable, several statistical methods can be used to answer the research question appropriately. This aspect of the data analysis plan outlines clearly why each statistical method will be used to test hypotheses. The level of statistical significance (p-value) which is often but not always <0.05 should also be written.  Presented in figures 2a and 2b are decision trees for some common statistical tests based on the variable type and research question

A good analysis plan should clearly describe how missing data will be analysed.

How to choose a statistical method to determine association between variables

7. Creating shell tables

Data analysis involves three levels of analysis; univariable, bivariable and multivariable analysis with increasing order of complexity. Shell tables should be created in anticipation for the results that will be obtained from these different levels of analysis. Read our blog article on how to present tables and figures for more details. Suppose you carry out a study to investigate the prevalence and associated factors of a certain disease “X” in a population, then the shell tables can be represented as in Tables 1, Table 2 and Table 3 below.

Table 1: Example of a shell table from univariate analysis

Example of a shell table from univariate analysis

Table 2: Example of a shell table from bivariate analysis

Example of a shell table from bivariate analysis

Table 3: Example of a shell table from multivariate analysis

Example of a shell table from multivariate analysis

aOR = adjusted odds ratio

Now that you have learned how to create a data analysis plan, these are the takeaway points. It should clearly state the:

  • Research question, objectives, and hypotheses
  • Dataset to be used
  • Variable types and their role
  • Statistical software and statistical methods
  • Shell tables for univariate, bivariate and multivariate analysis

Further readings

Creating a Data Analysis Plan: What to Consider When Choosing Statistics for a Study https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552232/pdf/cjhp-68-311.pdf

Creating an Analysis Plan: https://www.cdc.gov/globalhealth/healthprotection/fetp/training_modules/9/creating-analysis-plan_pw_final_09242013.pdf

Data Analysis Plan: https://www.statisticssolutions.com/dissertation-consulting-services/data-analysis-plan-2/

Photo created by freepik – www.freepik.com

Barche Blaise

Dr Barche is a physician and holds a Masters in Public Health. He is a senior fellow at CRENC with interests in Data Science and Data Analysis.

Post Navigation

16 comments.

Ewane Edwin, MD

Thanks. Quite informative.

James Tony

Educative write-up. Thanks.

Mabou Gabriel

Easy to understand. Thanks Dr

Amabo Miranda N.

Very explicit Dr. Thanks

Dongmo Roosvelt, MD

I will always remember how you help me conceptualize and understand data science in a simple way. I can only hope that someday I’ll be in a position to repay you, my dear friend.

Menda Blondelle

Plan d’analyse

Marc Lionel Ngamani

This is interesting, Thanks

Nkai

Very understandable and informative. Thank you..

Ndzeshang

love the figures.

Selemani C Ngwira

Nice, and informative

MONICA NAYEBARE

This is so much educative and good for beginners, I would love to recommend that you create and share a video because some people are able to grasp when there is an instructor. Lots of love

Kwasseu

Thank you Doctor very helpful.

Mbapah L. Tasha

Educative and clearly written. Thanks

Philomena Balera

Well said doctor,thank you.But when do you present in tables ,bars,pie chart etc?

Rasheda

Very informative guide!

Submit a Comment Cancel Reply

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

Notify me of follow-up comments by email.

Notify me of new posts by email.

Submit Comment

  Receive updates on new courses and blog posts

Never Miss a Thing!

Never Miss a Thing!

Subscribe to our mailing list to receive the latest news and updates on our webinars, articles and courses.

You have Successfully Subscribed!

Globalstats Academic

Statistic consultant for academic research.

Data Analysis in Quantitative Research Proposal

Data Analysis in Quantitative Research Proposal

Definition of data analysis.

Data analysis in quantitative research proposal is one part of the chapter that researchers need in the beginning of writing a research proposal. Whereas in the research, it is an activity after the data from all collected. Activities in data analysis are: grouping data based on variables and types of respondents, tabulating data based on variables from all respondents, presenting data for each variable studied, doing calculations to answer the problem formulation, and doing calculations to test the proposed hypothesis.

Quantitative Data Analysis Techniques

In a research proposal, it must be clear what method of analysis is capable of answering the research hypothesis. Hypothesis is a temporary answer to the research problem. Data analysis techniques in quantitative research commonly use statistics. There are two kinds of statistical data analysis in research. These are descriptive statistics and inferential statistics. Inferential statistics include parametric and non-parametric statistics.

Descriptive statistics

In preparing research proposals, researchers need to explain what is descriptive research. Descriptive statistic is a method to analyze data by describing data without intending to make generalizations. Descriptive statistics only describes the sample data and does not make conclusions that apply to the population. While, conclusion that applies to the population, then the data analysis technique is inferential statistics. In addition descriptive statistics also function to present information in such a way that data generated from research can be utilized by others in need.

Inferential Statistics

When researchers want to generalize broader conclusions in the research proposal, it is necessary to write inferential statistics. Inferential statistics (often also commonly inductive statistics or probability statistics) are statistical techniques used to analyze sample data and the results are applied to populations. It requires a random sampling process.

Inferential research involves statistical probability. Using of probability theory is to approach sample to the population. A conclusion applying to the population has a chance of error and truth level. If the chance of error is 5%, then the truth level is 95%. While the chance of error is 1%, then the truth level is 99%. This opportunity for error and truth is the level of significance. Statistical tables are useful for carrying out tests of the significance of this error. For example, t-test will use table-t. in each table provides significance level of what percentage of the results. For example the correlation analysis found a correlation coefficient of 0.54 and for a significance of 5% it means that a variable relationship of 0.54 can apply to 95 out of 100 samples taken from a population. Inferential statistics is a higher level then descriptive statistics. To that in the research proposal, the flow of conclusions becomes clear. Data Analysis is to make general conclusions (conclusions), make a prediction (prediction), or make an estimate (estimation).

  • Privacy Policy

Research Method

Home » How To Write A Research Proposal – Step-by-Step [Template]

How To Write A Research Proposal – Step-by-Step [Template]

Table of Contents

How To Write a Research Proposal

How To Write a Research Proposal

Writing a Research proposal involves several steps to ensure a well-structured and comprehensive document. 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. Introduction:

  • Provide an introduction to your research topic, highlighting its significance and relevance.
  • Clearly state the research problem or question you aim to address.
  • Discuss the background and context of the study, including previous research in the field.

3. Research Objectives

  • Outline the specific objectives or aims of your research. These objectives should be clear, achievable, and aligned with the research problem.

4. Literature Review:

  • Conduct a comprehensive review of relevant literature and studies related to your research topic.
  • Summarize key findings, identify gaps, and highlight how your research will contribute to the existing knowledge.

5. Methodology:

  • Describe the research design and methodology you plan to employ to address your research objectives.
  • Explain the data collection methods, instruments, and analysis techniques you will use.
  • Justify why the chosen methods are appropriate and suitable for your research.

6. Timeline:

  • Create a timeline or schedule that outlines the major milestones and activities of your research project.
  • Break down the research process into smaller tasks and estimate the time required for each task.

7. Resources:

  • Identify the resources needed for your research, such as access to specific databases, equipment, or funding.
  • Explain how you will acquire or utilize these resources to carry out your research effectively.

8. Ethical Considerations:

  • Discuss any ethical issues that may arise during your research and explain how you plan to address them.
  • If your research involves human subjects, explain how you will ensure their informed consent and privacy.

9. Expected Outcomes and Significance:

  • Clearly state the expected outcomes or results of your research.
  • Highlight the potential impact and significance of your research in advancing knowledge or addressing practical issues.

10. References:

  • Provide a list of all the references cited in your proposal, following a consistent citation style (e.g., APA, MLA).

11. Appendices:

  • Include any additional supporting materials, such as survey questionnaires, interview guides, or data analysis plans.

Research Proposal Format

The format of a research proposal may vary depending on the specific requirements of the institution or funding agency. However, the following is a commonly used format for a research proposal:

1. Title Page:

  • Include the title of your research proposal, your name, your affiliation or institution, and the date.

2. Abstract:

  • Provide a brief summary of your research proposal, highlighting the research problem, objectives, methodology, and expected outcomes.

3. Introduction:

  • Introduce the research topic and provide background information.
  • State the research problem or question you aim to address.
  • Explain the significance and relevance of the research.
  • Review relevant literature and studies related to your research topic.
  • Summarize key findings and identify gaps in the existing knowledge.
  • Explain how your research will contribute to filling those gaps.

5. Research Objectives:

  • Clearly state the specific objectives or aims of your research.
  • Ensure that the objectives are clear, focused, and aligned with the research problem.

6. Methodology:

  • Describe the research design and methodology you plan to use.
  • Explain the data collection methods, instruments, and analysis techniques.
  • Justify why the chosen methods are appropriate for your research.

7. Timeline:

8. Resources:

  • Explain how you will acquire or utilize these resources effectively.

9. Ethical Considerations:

  • If applicable, explain how you will ensure informed consent and protect the privacy of research participants.

10. Expected Outcomes and Significance:

11. References:

12. Appendices:

Research Proposal Template

Here’s a template for a research proposal:

1. Introduction:

2. Literature Review:

3. Research Objectives:

4. Methodology:

5. Timeline:

6. Resources:

7. Ethical Considerations:

8. Expected Outcomes and Significance:

9. References:

10. Appendices:

Research Proposal Sample

Title: The Impact of Online Education on Student Learning Outcomes: A Comparative Study

1. Introduction

Online education has gained significant prominence in recent years, especially due to the COVID-19 pandemic. This research proposal aims to investigate the impact of online education on student learning outcomes by comparing them with traditional face-to-face instruction. The study will explore various aspects of online education, such as instructional methods, student engagement, and academic performance, to provide insights into the effectiveness of online learning.

2. Objectives

The main objectives of this research are as follows:

  • To compare student learning outcomes between online and traditional face-to-face education.
  • To examine the factors influencing student engagement in online learning environments.
  • To assess the effectiveness of different instructional methods employed in online education.
  • To identify challenges and opportunities associated with online education and suggest recommendations for improvement.

3. Methodology

3.1 Study Design

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

The research will involve undergraduate students from two universities, one offering online education and the other providing face-to-face instruction. A total of 500 students (250 from each university) will be selected randomly to participate in the study.

3.3 Data Collection

The research will employ the following data collection methods:

  • Quantitative: Pre- and post-assessments will be conducted to measure students’ learning outcomes. Data on student demographics and academic performance will also be collected from university records.
  • Qualitative: Focus group discussions and individual interviews will be conducted with students to gather their perceptions and experiences regarding online education.

3.4 Data Analysis

Quantitative data will be analyzed using statistical software, employing descriptive statistics, t-tests, and regression analysis. Qualitative data will be transcribed, coded, and analyzed thematically to identify recurring patterns and themes.

4. Ethical Considerations

The study will adhere to ethical guidelines, ensuring the privacy and confidentiality of participants. Informed consent will be obtained, and participants will have the right to withdraw from the study at any time.

5. Significance and Expected Outcomes

This research will contribute to the existing literature by providing empirical evidence on the impact of online education on student learning outcomes. The findings will help educational institutions and policymakers make informed decisions about incorporating online learning methods and improving the quality of online education. Moreover, the study will identify potential challenges and opportunities related to online education and offer recommendations for enhancing student engagement and overall learning outcomes.

6. Timeline

The proposed research will be conducted over a period of 12 months, including data collection, analysis, and report writing.

The estimated budget for this research includes expenses related to data collection, software licenses, participant compensation, and research assistance. A detailed budget breakdown will be provided in the final research plan.

8. Conclusion

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. By exploring various dimensions of online education, this research will provide valuable insights into the effectiveness and challenges associated with online learning. The findings will contribute to the ongoing discourse on educational practices and help shape future strategies for maximizing student learning outcomes in online education settings.

About the author

' src=

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

How To Write A Proposal

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

Grant Proposal

Grant Proposal – Example, Template and Guide

How To Write A Business Proposal

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

Business Proposal

Business Proposal – Templates, Examples and Guide

Proposal

Proposal – Types, Examples, and Writing Guide

How to choose an Appropriate Method for Research?

How to choose an Appropriate Method for Research?

SlideTeam

Researched by Consultants from Top-Tier Management Companies

Banner Image

Powerpoint Templates

Icon Bundle

Kpi Dashboard

Professional

Business Plans

Swot Analysis

Gantt Chart

Business Proposal

Marketing Plan

Project Management

Business Case

Business Model

Cyber Security

Business PPT

Digital Marketing

Digital Transformation

Human Resources

Product Management

Artificial Intelligence

Company Profile

Acknowledgement PPT

PPT Presentation

Reports Brochures

One Page Pitch

Interview PPT

All Categories

Top 10 Data Analysis Research Proposal Templates with Examples and Samples

Top 10 Data Analysis Research Proposal Templates with Examples and Samples

Himani Khatri

author-user

In a world awash with data, the real challenge lies not in the abundance of information but in deciphering its true meaning, making sense of the chaos, and addressing pressing real-world problems. If you're a researcher or student, you know the struggle: the pain points of grappling with data quality, precision, and relevance. It's these very challenges that underscore the critical importance of crafting a well-structured data analysis research proposal.

Think of it as your toolkit, a roadmap to navigate the complexities of data-driven research and turn information into solutions. In this blog, we're here to help you master the art of creating a data analysis research proposal, providing you with the key to unlock the answers to those nagging questions, and offer solutions (Our editable templates) to problems that keep you up at night.

As we start this journey, let's draw inspiration from two illustrious examples, Google Flu Trends and Netflix's Recommendation Algorithm, which have not only captured the limelight but have tackled data-related pain points and transformed them into remarkable solutions. These examples will serve as guiding stars as we navigate the intricacies of data analysis to craft proposals that address real-world issues head-on.

Google Flu Trends : Conquering the Challenge of Data Accuracy

Imagine having the power to predict flu outbreaks with uncanny precision. Google Flu Trends did just that, tapping into the vast sea of search queries. But it wasn't just about innovation; it was also about recognizing the persistent pain point of data accuracy and modeling. The project revealed that behind every data analysis success story lies the challenge of ensuring data quality and building models that stand up to the rigorous demands of real-world problems.

Netflix's Recommendation Algorithm : Navigating the Data Overload Dilemma

In the world of entertainment, where options seem endless, Netflix's Recommendation Algorithm emerged as a winner. It tackled the overwhelming pain point of information overload by leveraging data to understand users better. The result? A recommendation system that not only improved user satisfaction but also demonstrated how data analysis can help individuals navigate through the ever-growing sea of choices and make their lives easier.

In these two case studies, we uncover the real-world challenges that data analysis can address, from accuracy dilemmas to information overload.

Let's explore the research proposal presentation templates now!

Template 1: Data Analysis in Research Proposal

Data Analysis in Research Proposal

Click Here to Download

Introducing this cover slide of the proposal that has been professionally designed and sets the stage for your entire research proposal. With ample space for an image, it captures your audience's attention from the start. Your proposal's credentials, both for the recipient and the preparer, can be displayed. Both researchers and professionals can take assistance to streamline the presentation creation process, leaving you more time to focus on your data analysis. Make a lasting impression and get your proposal noticed with this polished, easy-to-use template.

Template 2: Cover Letter for Research Data Analysis Proposal

Cover Letter for Research Data Analysis Proposal

Introducing this Cover Letter Slide, which will help you make a lasting impression in the world of research and analytics. We understand the importance of clear and concise communication in proposals. Our professionally crafted slide provides a perfect introduction, addressing your customers and outlining your company's objectives. Say goodbye to the hassle of creating proposals from scratch – with our ready-made slide, you can simply insert your details and be on your way to success. This cover letter helps you state that your experience and expertise will help your audience achieve their goals effortlessly. Don't miss this opportunity – grab this proposal slide and make a strong, confident start in the world of data analytics.

Template 3 – Project Context and Objectives of Research Data Analysis Proposal

Project Context and Objectives of Research Data Analysis Proposal

This slide simplifies the process of impressing your clients. It explains your project's context and objectives, leaving a lasting impact on your audience.

Project Context: We provide a clear and concise space for explaining the background and significance of your research, setting the stage for your proposal.

Project Objectives: Clearly outline your research goals and what you aim to achieve, ensuring everyone understands your mission.

Make your research proposal shine with this template at your disposal.

Template 4: Scope of Work for Research Data Analysis Proposal

Scope of Work for Research Data Analysis Proposal

This slide outlines your research data analysis journey, making client presentations a breeze. Our scope of work slide covers all the essentials: Acquisition & Extraction, Examination, Cleaning, Transformation, Exploration, and Analysis, leading to the grand finale - Presenting and Sharing your findings. With clear and easy-to-understand visuals, impress your clients and streamline your workflow.

Template 5: Plan of Action for Research Data Analysis Proposal

Plan of Action for Research Data Analysis Proposal

Are you looking to present your research data analysis plan with clarity and professionalism? Our ready-made PowerPoint slide has got you covered. This user-friendly template features a visual diagram illustrating the entire process, from data collection through pre-processing, analysis, and classification. With easy-to-understand icons and clear labels, you can effectively convey your plan to your audience.

Template 6: Timeline for Research Data Analysis Project

Designed with simplicity, this timeline slide offers a user-friendly layout to help you convey complex ideas easily. It covers every crucial step of your analysis journey, from tackling business issues to final presentation. With vibrant visuals and customizable elements, you can effortlessly illustrate data understanding, preparation, exploratory analysis, validation, and visualization. Get it today!

Timeline for Research Data Analysis Project

Template 7: Key Deliverables for Research Data Analysis Proposal

With clear, concise visuals, this slide presents your key deliverables. From ‘Decision Mapping’ that outlines your project's path to ‘Analysis and Design’ for robust strategies, and ‘Implementation’ for real-world action, it's all here. Even better, it highlights ‘Ongoing Steps’ for sustained success. Why waste time on complex slides when you can have this ready-made gem? Elevate your presentations and win your audience over with this template at your disposal.

Key Deliverables for Research Data Analysis Proposal

Template 8: Why Our Data Analytics Company?

This slide helps you showcase why people should choose your company rather than your competitors. Elucidate what makes your organization stand out from the rest by taking assistance of this readily-available PowerPoint slide. 

It lists down the strength that keeps your firm on the top in comparison with your rivals.

Some of the strengths mentioned in the slide are:

  • Reduced churn rate
  • Reduced operational cost
  • Increased revenue
  • Faster data analysis reporting

Why Our Data Analytics Company

Template 9: Services Offered by Data Analytics Company 

This slide presents the services offered by data analysis company in a clear and precise way. Get your hands on this slide to present your offerings. The template encapsulates services like data collection services, data quality assess, data integration, policy analytics, social media and digital outreach, enterprise analytics, and more.

Services Offered by Data Analytics Company

Template 10: Team Structure of Data Analysis Company

The slide presents team structure of data analytics company in a comprehensive format. A hierarchy chart makes it easy for organization to showcase their talented staff and the driving forces behind their firm’s success, this is where this template comes into assistance. Put your hands on this template to present head of advanced analytics, COE Support office, demand management, analytics development, analytics support, etc.

Team Structure of Data Analysis Company 1/2

These templates are your one-stop solution for crafting compelling Research Data Analysis Proposals.

With a subscription to our service, you gain access to an extensive library of ready-made PowerPoint templates that will save you time and effort. But that's not all – if you require a personalized touch, our team can also design a custom proposal that perfectly aligns with your unique needs.

Why wait? Join our community of satisfied customers and supercharge your research endeavors today.

Subscribe now and get your hands on impactful presentations!

Related posts:

  • How to Design the Perfect Service Launch Presentation [Custom Launch Deck Included]
  • Quarterly Business Review Presentation: All the Essential Slides You Need in Your Deck
  • [Updated 2023] How to Design The Perfect Product Launch Presentation [Best Templates Included]
  • 99% of the Pitches Fail! Find Out What Makes Any Startup a Success

Liked this blog? Please recommend us

how to make data analysis in research proposal

Must-Have Acquisition Proposal Templates With Examples and Samples

Top 10 Organizational Plan Templates with Samples and Examples

Top 10 Organizational Plan Templates with Samples and Examples

This form is protected by reCAPTCHA - the Google Privacy Policy and Terms of Service apply.

digital_revolution_powerpoint_presentation_slides_Slide01

Digital revolution powerpoint presentation slides

sales_funnel_results_presentation_layouts_Slide01

Sales funnel results presentation layouts

3d_men_joinning_circular_jigsaw_puzzles_ppt_graphics_icons_Slide01

3d men joinning circular jigsaw puzzles ppt graphics icons

Business Strategic Planning Template For Organizations Powerpoint Presentation Slides

Business Strategic Planning Template For Organizations Powerpoint Presentation Slides

Future plan powerpoint template slide

Future plan powerpoint template slide

project_management_team_powerpoint_presentation_slides_Slide01

Project Management Team Powerpoint Presentation Slides

Brand marketing powerpoint presentation slides

Brand marketing powerpoint presentation slides

Launching a new service powerpoint presentation with slides go to market

Launching a new service powerpoint presentation with slides go to market

agenda_powerpoint_slide_show_Slide01

Agenda powerpoint slide show

Four key metrics donut chart with percentage

Four key metrics donut chart with percentage

Engineering and technology ppt inspiration example introduction continuous process improvement

Engineering and technology ppt inspiration example introduction continuous process improvement

Meet our team representing in circular format

Meet our team representing in circular format

Google Reviews

We use essential cookies to make Venngage work. By clicking “Accept All Cookies”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts.

Manage Cookies

Cookies and similar technologies collect certain information about how you’re using our website. Some of them are essential, and without them you wouldn’t be able to use Venngage. But others are optional, and you get to choose whether we use them or not.

Strictly Necessary Cookies

These cookies are always on, as they’re essential for making Venngage work, and making it safe. Without these cookies, services you’ve asked for can’t be provided.

Show cookie providers

  • Google Login

Functionality Cookies

These cookies help us provide enhanced functionality and personalisation, and remember your settings. They may be set by us or by third party providers.

Performance Cookies

These cookies help us analyze how many people are using Venngage, where they come from and how they're using it. If you opt out of these cookies, we can’t get feedback to make Venngage better for you and all our users.

  • Google Analytics

Targeting Cookies

These cookies are set by our advertising partners to track your activity and show you relevant Venngage ads on other sites as you browse the internet.

  • Google Tag Manager
  • Infographics
  • Daily Infographics
  • Template Lists
  • Graphic Design
  • Graphs and Charts
  • Data Visualization
  • Human Resources
  • Beginner Guides

Blog Business How to Write a Research Proposal: A Step-by-Step

How to Write a Research Proposal: A Step-by-Step

Written by: Danesh Ramuthi Nov 29, 2023

How to Write a Research Proposal

A research proposal is a structured outline for a planned study on a specific topic. It serves as a roadmap, guiding researchers through the process of converting their research idea into a feasible project. 

The aim of a research proposal is multifold: it articulates the research problem, establishes a theoretical framework, outlines the research methodology and highlights the potential significance of the study. Importantly, it’s a critical tool for scholars seeking grant funding or approval for their research projects.

Crafting a good research proposal requires not only understanding your research topic and methodological approaches but also the ability to present your ideas clearly and persuasively. Explore Venngage’s Proposal Maker and Research Proposals Templates to begin your journey in writing a compelling research proposal.

What to include in a research proposal?

In a research proposal, include a clear statement of your research question or problem, along with an explanation of its significance. This should be followed by a literature review that situates your proposed study within the context of existing research. 

Your proposal should also outline the research methodology, detailing how you plan to conduct your study, including data collection and analysis methods.

Additionally, include a theoretical framework that guides your research approach, a timeline or research schedule, and a budget if applicable. It’s important to also address the anticipated outcomes and potential implications of your study. A well-structured research proposal will clearly communicate your research objectives, methods and significance to the readers.

Light Blue Shape Semiotic Analysis Research Proposal

How to format a research proposal?

Formatting a research proposal involves adhering to a structured outline to ensure clarity and coherence. While specific requirements may vary, a standard research proposal typically includes the following elements:

  • Title Page: Must include the title of your research proposal, your name and affiliations. The title should be concise and descriptive of your proposed research.
  • Abstract: A brief summary of your proposal, usually not exceeding 250 words. It should highlight the research question, methodology and the potential impact of the study.
  • Introduction: Introduces your research question or problem, explains its significance, and states the objectives of your study.
  • Literature review: Here, you contextualize your research within existing scholarship, demonstrating your knowledge of the field and how your research will contribute to it.
  • Methodology: Outline your research methods, including how you will collect and analyze data. This section should be detailed enough to show the feasibility and thoughtfulness of your approach.
  • Timeline: Provide an estimated schedule for your research, breaking down the process into stages with a realistic timeline for each.
  • Budget (if applicable): If your research requires funding, include a detailed budget outlining expected cost.
  • References/Bibliography: List all sources referenced in your proposal in a consistent citation style.

Green And Orange Modern Research Proposal

How to write a research proposal in 11 steps?

Writing a research proposal in structured steps ensures a comprehensive and coherent presentation of your research project. Let’s look at the explanation for each of the steps here:  

Step 1: Title and Abstract Step 2: Introduction Step 3: Research objectives Step 4: Literature review Step 5: Methodology Step 6: Timeline Step 7: Resources Step 8: Ethical considerations Step 9: Expected outcomes and significance Step 10: References Step 11: Appendices

Step 1: title and abstract.

Select a concise, descriptive title and write an abstract summarizing your research question, objectives, methodology and expected outcomes​​. The abstract should include your research question, the objectives you aim to achieve, the methodology you plan to employ and the anticipated outcomes. 

Step 2: Introduction

In this section, introduce the topic of your research, emphasizing its significance and relevance to the field. Articulate the research problem or question in clear terms and provide background context, which should include an overview of previous research in the field.

Step 3: Research objectives

Here, you’ll need to outline specific, clear and achievable objectives that align with your research problem. These objectives should be well-defined, focused and measurable, serving as the guiding pillars for your study. They help in establishing what you intend to accomplish through your research and provide a clear direction for your investigation.

Step 4: Literature review

In this part, conduct a thorough review of existing literature related to your research topic. This involves a detailed summary of key findings and major contributions from previous research. Identify existing gaps in the literature and articulate how your research aims to fill these gaps. The literature review not only shows your grasp of the subject matter but also how your research will contribute new insights or perspectives to the field.

Step 5: Methodology

Describe the design of your research and the methodologies you will employ. This should include detailed information on data collection methods, instruments to be used and analysis techniques. Justify the appropriateness of these methods for your research​​.

Step 6: Timeline

Construct a detailed timeline that maps out the major milestones and activities of your research project. Break the entire research process into smaller, manageable tasks and assign realistic time frames to each. This timeline should cover everything from the initial research phase to the final submission, including periods for data collection, analysis and report writing. 

It helps in ensuring your project stays on track and demonstrates to reviewers that you have a well-thought-out plan for completing your research efficiently.

Step 7: Resources

Identify all the resources that will be required for your research, such as specific databases, laboratory equipment, software or funding. Provide details on how these resources will be accessed or acquired. 

If your research requires funding, explain how it will be utilized effectively to support various aspects of the project. 

Step 8: Ethical considerations

Address any ethical issues that may arise during your research. This is particularly important for research involving human subjects. Describe the measures you will take to ensure ethical standards are maintained, such as obtaining informed consent, ensuring participant privacy, and adhering to data protection regulations. 

Here, in this section you should reassure reviewers that you are committed to conducting your research responsibly and ethically.

Step 9: Expected outcomes and significance

Articulate the expected outcomes or results of your research. Explain the potential impact and significance of these outcomes, whether in advancing academic knowledge, influencing policy or addressing specific societal or practical issues. 

Step 10: References

Compile a comprehensive list of all the references cited in your proposal. Adhere to a consistent citation style (like APA or MLA) throughout your document. The reference section not only gives credit to the original authors of your sourced information but also strengthens the credibility of your proposal.

Step 11: Appendices

Include additional supporting materials that are pertinent to your research proposal. This can be survey questionnaires, interview guides, detailed data analysis plans or any supplementary information that supports the main text. 

Appendices provide further depth to your proposal, showcasing the thoroughness of your preparation.

Beige And Dark Green Minimalist Research Proposal

Research proposal FAQs

1. how long should a research proposal be.

The length of a research proposal can vary depending on the requirements of the academic institution, funding body or specific guidelines provided. Generally, research proposals range from 500 to 1500 words or about one to a few pages long. It’s important to provide enough detail to clearly convey your research idea, objectives and methodology, while being concise. Always check

2. Why is the research plan pivotal to a research project?

The research plan is pivotal to a research project because it acts as a blueprint, guiding every phase of the study. It outlines the objectives, methodology, timeline and expected outcomes, providing a structured approach and ensuring that the research is systematically conducted. 

A well-crafted plan helps in identifying potential challenges, allocating resources efficiently and maintaining focus on the research goals. It is also essential for communicating the project’s feasibility and importance to stakeholders, such as funding bodies or academic supervisors.

Simple Minimalist White Research Proposal

Mastering how to write a research proposal is an essential skill for any scholar, whether in social and behavioral sciences, academic writing or any field requiring scholarly research. From this article, you have learned key components, from the literature review to the research design, helping you develop a persuasive and well-structured proposal.

Remember, a good research proposal not only highlights your proposed research and methodology but also demonstrates its relevance and potential impact.

For additional support, consider utilizing Venngage’s Proposal Maker and Research Proposals Templates , valuable tools in crafting a compelling proposal that stands out.

Whether it’s for grant funding, a research paper or a dissertation proposal, these resources can assist in transforming your research idea into a successful submission.

Discover popular designs

how to make data analysis in research proposal

Brochure maker

how to make data analysis in research proposal

White paper online

how to make data analysis in research proposal

Newsletter creator

how to make data analysis in research proposal

Flyer maker

how to make data analysis in research proposal

Timeline maker

how to make data analysis in research proposal

Letterhead maker

how to make data analysis in research proposal

Mind map maker

how to make data analysis in research proposal

Ebook maker

Grad Coach

What (Exactly) Is A Research Proposal?

A simple explainer with examples + free template.

By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020 (Updated April 2023)

Whether you’re nearing the end of your degree and your dissertation is on the horizon, or you’re planning to apply for a PhD program, chances are you’ll need to craft a convincing research proposal . If you’re on this page, you’re probably unsure exactly what the research proposal is all about. Well, you’ve come to the right place.

Overview: Research Proposal Basics

  • What a research proposal is
  • What a research proposal needs to cover
  • How to structure your research proposal
  • Example /sample proposals
  • Proposal writing FAQs
  • Key takeaways & additional resources

What is a research proposal?

Simply put, a research proposal is a structured, formal document that explains what you plan to research (your research topic), why it’s worth researching (your justification), and how  you plan to investigate it (your methodology). 

The purpose of the research proposal (its job, so to speak) is to convince  your research supervisor, committee or university that your research is  suitable  (for the requirements of the degree program) and  manageable  (given the time and resource constraints you will face). 

The most important word here is “ convince ” – in other words, your research proposal needs to  sell  your research idea (to whoever is going to approve it). If it doesn’t convince them (of its suitability and manageability), you’ll need to revise and resubmit . This will cost you valuable time, which will either delay the start of your research or eat into its time allowance (which is bad news). 

A research proposal is a  formal document that explains what you plan to research , why it's worth researching and how you'll do it.

What goes into a research proposal?

A good dissertation or thesis proposal needs to cover the “ what “, “ why ” and” how ” of the proposed study. Let’s look at each of these attributes in a little more detail:

Your proposal needs to clearly articulate your research topic . This needs to be specific and unambiguous . Your research topic should make it clear exactly what you plan to research and in what context. Here’s an example of a well-articulated research topic:

An investigation into the factors which impact female Generation Y consumer’s likelihood to promote a specific makeup brand to their peers: a British context

As you can see, this topic is extremely clear. From this one line we can see exactly:

  • What’s being investigated – factors that make people promote or advocate for a brand of a specific makeup brand
  • Who it involves – female Gen-Y consumers
  • In what context – the United Kingdom

So, make sure that your research proposal provides a detailed explanation of your research topic . If possible, also briefly outline your research aims and objectives , and perhaps even your research questions (although in some cases you’ll only develop these at a later stage). Needless to say, don’t start writing your proposal until you have a clear topic in mind , or you’ll end up waffling and your research proposal will suffer as a result of this.

Need a helping hand?

how to make data analysis in research proposal

As we touched on earlier, it’s not good enough to simply propose a research topic – you need to justify why your topic is original . In other words, what makes it  unique ? What gap in the current literature does it fill? If it’s simply a rehash of the existing research, it’s probably not going to get approval – it needs to be fresh.

But,  originality  alone is not enough. Once you’ve ticked that box, you also need to justify why your proposed topic is  important . In other words, what value will it add to the world if you achieve your research aims?

As an example, let’s look at the sample research topic we mentioned earlier (factors impacting brand advocacy). In this case, if the research could uncover relevant factors, these findings would be very useful to marketers in the cosmetics industry, and would, therefore, have commercial value . That is a clear justification for the research.

So, when you’re crafting your research proposal, remember that it’s not enough for a topic to simply be unique. It needs to be useful and value-creating – and you need to convey that value in your proposal. If you’re struggling to find a research topic that makes the cut, watch  our video covering how to find a research topic .

Free Webinar: How To Write A Research Proposal

It’s all good and well to have a great topic that’s original and valuable, but you’re not going to convince anyone to approve it without discussing the practicalities – in other words:

  • How will you actually undertake your research (i.e., your methodology)?
  • Is your research methodology appropriate given your research aims?
  • Is your approach manageable given your constraints (time, money, etc.)?

While it’s generally not expected that you’ll have a fully fleshed-out methodology at the proposal stage, you’ll likely still need to provide a high-level overview of your research methodology . Here are some important questions you’ll need to address in your research proposal:

  • Will you take a qualitative , quantitative or mixed -method approach?
  • What sampling strategy will you adopt?
  • How will you collect your data (e.g., interviews, surveys, etc)?
  • How will you analyse your data (e.g., descriptive and inferential statistics , content analysis, discourse analysis, etc, .)?
  • What potential limitations will your methodology carry?

So, be sure to give some thought to the practicalities of your research and have at least a basic methodological plan before you start writing up your proposal. If this all sounds rather intimidating, the video below provides a good introduction to research methodology and the key choices you’ll need to make.

How To Structure A Research Proposal

Now that we’ve covered the key points that need to be addressed in a proposal, you may be wondering, “ But how is a research proposal structured? “.

While the exact structure and format required for a research proposal differs from university to university, there are four “essential ingredients” that commonly make up the structure of a research proposal:

  • A rich introduction and background to the proposed research
  • An initial literature review covering the existing research
  • An overview of the proposed research methodology
  • A discussion regarding the practicalities (project plans, timelines, etc.)

In the video below, we unpack each of these four sections, step by step.

Research Proposal Examples/Samples

In the video below, we provide a detailed walkthrough of two successful research proposals (Master’s and PhD-level), as well as our popular free proposal template.

Proposal Writing FAQs

How long should a research proposal be.

This varies tremendously, depending on the university, the field of study (e.g., social sciences vs natural sciences), and the level of the degree (e.g. undergraduate, Masters or PhD) – so it’s always best to check with your university what their specific requirements are before you start planning your proposal.

As a rough guide, a formal research proposal at Masters-level often ranges between 2000-3000 words, while a PhD-level proposal can be far more detailed, ranging from 5000-8000 words. In some cases, a rough outline of the topic is all that’s needed, while in other cases, universities expect a very detailed proposal that essentially forms the first three chapters of the dissertation or thesis.

The takeaway – be sure to check with your institution before you start writing.

How do I choose a topic for my research proposal?

Finding a good research topic is a process that involves multiple steps. We cover the topic ideation process in this video post.

How do I write a literature review for my proposal?

While you typically won’t need a comprehensive literature review at the proposal stage, you still need to demonstrate that you’re familiar with the key literature and are able to synthesise it. We explain the literature review process here.

How do I create a timeline and budget for my proposal?

We explain how to craft a project plan/timeline and budget in Research Proposal Bootcamp .

Which referencing format should I use in my research proposal?

The expectations and requirements regarding formatting and referencing vary from institution to institution. Therefore, you’ll need to check this information with your university.

What common proposal writing mistakes do I need to look out for?

We’ve create a video post about some of the most common mistakes students make when writing a proposal – you can access that here . If you’re short on time, here’s a quick summary:

  • The research topic is too broad (or just poorly articulated).
  • The research aims, objectives and questions don’t align.
  • The research topic is not well justified.
  • The study has a weak theoretical foundation.
  • The research design is not well articulated well enough.
  • Poor writing and sloppy presentation.
  • Poor project planning and risk management.
  • Not following the university’s specific criteria.

Key Takeaways & Additional Resources

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. While we’ve covered the essentials here, every institution has its own set of expectations and it’s essential that you follow these to maximise your chances of approval.

By the way, we’ve got plenty more resources to help you fast-track your research proposal. Here are some of our most popular resources to get you started:

  • Proposal Writing 101 : A Introductory Webinar
  • Research Proposal Bootcamp : The Ultimate Online Course
  • Template : A basic template to help you craft your proposal

If you’re looking for 1-on-1 support with your research proposal, be sure to check out our private coaching service , where we hold your hand through the proposal development process (and the entire research journey), step by step.

Literature Review Course

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:

Thematic analysis 101

51 Comments

Myrna Pereira

I truly enjoyed this video, as it was eye-opening to what I have to do in the preparation of preparing a Research proposal.

I would be interested in getting some coaching.

BARAKAELI TEREVAELI

I real appreciate on your elaboration on how to develop research proposal,the video explains each steps clearly.

masebo joseph

Thank you for the video. It really assisted me and my niece. I am a PhD candidate and she is an undergraduate student. It is at times, very difficult to guide a family member but with this video, my job is done.

In view of the above, I welcome more coaching.

Zakia Ghafoor

Wonderful guidelines, thanks

Annie Malupande

This is very helpful. Would love to continue even as I prepare for starting my masters next year.

KYARIKUNDA MOREEN

Thanks for the work done, the text was helpful to me

Ahsanullah Mangal

Bundle of thanks to you for the research proposal guide it was really good and useful if it is possible please send me the sample of research proposal

Derek Jansen

You’re most welcome. We don’t have any research proposals that we can share (the students own the intellectual property), but you might find our research proposal template useful: https://gradcoach.com/research-proposal-template/

Cheruiyot Moses Kipyegon

Cheruiyot Moses Kipyegon

Thanks alot. It was an eye opener that came timely enough before my imminent proposal defense. Thanks, again

agnelius

thank you very much your lesson is very interested may God be with you

Abubakar

I am an undergraduate student (First Degree) preparing to write my project,this video and explanation had shed more light to me thanks for your efforts keep it up.

Synthia Atieno

Very useful. I am grateful.

belina nambeya

this is a very a good guidance on research proposal, for sure i have learnt something

Wonderful guidelines for writing a research proposal, I am a student of m.phil( education), this guideline is suitable for me. Thanks

You’re welcome 🙂

Marjorie

Thank you, this was so helpful.

Amitash Degan

A really great and insightful video. It opened my eyes as to how to write a research paper. I would like to receive more guidance for writing my research paper from your esteemed faculty.

Glaudia Njuguna

Thank you, great insights

Thank you, great insights, thank you so much, feeling edified

Yebirgual

Wow thank you, great insights, thanks a lot

Roseline Soetan

Thank you. This is a great insight. I am a student preparing for a PhD program. I am requested to write my Research Proposal as part of what I am required to submit before my unconditional admission. I am grateful having listened to this video which will go a long way in helping me to actually choose a topic of interest and not just any topic as well as to narrow down the topic and be specific about it. I indeed need more of this especially as am trying to choose a topic suitable for a DBA am about embarking on. Thank you once more. The video is indeed helpful.

Rebecca

Have learnt a lot just at the right time. Thank you so much.

laramato ikayo

thank you very much ,because have learn a lot things concerning research proposal and be blessed u for your time that you providing to help us

Cheruiyot M Kipyegon

Hi. For my MSc medical education research, please evaluate this topic for me: Training Needs Assessment of Faculty in Medical Training Institutions in Kericho and Bomet Counties

Rebecca

I have really learnt a lot based on research proposal and it’s formulation

Arega Berlie

Thank you. I learn much from the proposal since it is applied

Siyanda

Your effort is much appreciated – you have good articulation.

You have good articulation.

Douglas Eliaba

I do applaud your simplified method of explaining the subject matter, which indeed has broaden my understanding of the subject matter. Definitely this would enable me writing a sellable research proposal.

Weluzani

This really helping

Roswitta

Great! I liked your tutoring on how to find a research topic and how to write a research proposal. Precise and concise. Thank you very much. Will certainly share this with my students. Research made simple indeed.

Alice Kuyayama

Thank you very much. I an now assist my students effectively.

Thank you very much. I can now assist my students effectively.

Abdurahman Bayoh

I need any research proposal

Silverline

Thank you for these videos. I will need chapter by chapter assistance in writing my MSc dissertation

Nosi

Very helpfull

faith wugah

the videos are very good and straight forward

Imam

thanks so much for this wonderful presentations, i really enjoyed it to the fullest wish to learn more from you

Bernie E. Balmeo

Thank you very much. I learned a lot from your lecture.

Ishmael kwame Appiah

I really enjoy the in-depth knowledge on research proposal you have given. me. You have indeed broaden my understanding and skills. Thank you

David Mweemba

interesting session this has equipped me with knowledge as i head for exams in an hour’s time, am sure i get A++

Andrea Eccleston

This article was most informative and easy to understand. I now have a good idea of how to write my research proposal.

Thank you very much.

Georgina Ngufan

Wow, this literature is very resourceful and interesting to read. I enjoyed it and I intend reading it every now then.

Charity

Thank you for the clarity

Mondika Solomon

Thank you. Very helpful.

BLY

Thank you very much for this essential piece. I need 1o1 coaching, unfortunately, your service is not available in my country. Anyways, a very important eye-opener. I really enjoyed it. A thumb up to Gradcoach

Md Moneruszzaman Kayes

What is JAM? Please explain.

Gentiana

Thank you so much for these videos. They are extremely helpful! God bless!

azeem kakar

very very wonderful…

Koang Kuany Bol Nyot

thank you for the video but i need a written example

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

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

  • Knowledge Base
  • Research process
  • How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on 30 October 2022 by Shona McCombes and Tegan George. Revised on 13 June 2023.

Structure of a research proposal

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

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 organised and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, frequently asked questions.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

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

Prevent plagiarism, run a free check.

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’
  • Example research proposal #2: ‘ Medical Students as Mediators of Change in Tobacco Use’

Like your dissertation or thesis, the proposal will usually have a title page that includes:

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

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 your research will 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 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:

  • 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 synthesise prior scholarship

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.

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:

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

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

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:

  • Cost : exactly how much money do you need?
  • Justification : why is this cost necessary to complete the research?
  • Source : how did you calculate the amount?

To determine your budget, think about:

  • Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
  • Materials : do you need access to any tools or technologies?
  • Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

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.

Cite this Scribbr article

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 6 May 2024, from https://www.scribbr.co.uk/the-research-process/research-proposal-explained/

Is this article helpful?

Shona McCombes

Shona McCombes

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.

Organizing Your Social Sciences Research Assignments

  • Annotated Bibliography
  • Analyzing a Scholarly Journal Article
  • Group Presentations
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • Types of Structured Group Activities
  • Group Project Survival Skills
  • Leading a Class Discussion
  • Multiple Book Review Essay
  • Reviewing Collected Works
  • Writing a Case Analysis Paper
  • Writing a Case Study
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Reflective Paper
  • Writing a Research Proposal
  • Generative AI and Writing
  • Acknowledgments

The goal of a research proposal is twofold: to present and justify the need to study a research problem and to present the practical ways in which the proposed study should be conducted. The design elements and procedures for conducting research are governed by standards of the predominant discipline in which the problem resides, therefore, the guidelines for research proposals are more exacting and less formal than a general project proposal. Research proposals contain extensive literature reviews. They must provide persuasive evidence that a need exists for the proposed study. In addition to providing a rationale, a proposal describes detailed methodology for conducting the research consistent with requirements of the professional or academic field and a statement on anticipated outcomes and benefits derived from the study's completion.

Krathwohl, David R. How to Prepare a Dissertation Proposal: Suggestions for Students in Education and the Social and Behavioral Sciences . Syracuse, NY: Syracuse University Press, 2005.

How to Approach Writing a Research Proposal

Your professor may assign the task of writing a research proposal for the following reasons:

  • Develop your skills in thinking about and designing a comprehensive research study;
  • Learn how to conduct a comprehensive review of the literature to determine that the research problem has not been adequately addressed or has been answered ineffectively and, in so doing, become better at locating pertinent scholarship related to your topic;
  • Improve your general research and writing skills;
  • Practice identifying the logical steps that must be taken to accomplish one's research goals;
  • Critically review, examine, and consider the use of different methods for gathering and analyzing data related to the research problem; and,
  • Nurture a sense of inquisitiveness within yourself and to help see yourself as an active participant in the process of conducting scholarly research.

A proposal should contain all the key elements involved in designing a completed research study, with sufficient information that allows readers to assess the validity and usefulness of your proposed study. The only elements missing from a research proposal are the findings of the study and your analysis of those findings. Finally, an effective proposal is judged on the quality of your writing and, therefore, it is important that your proposal is coherent, clear, and compelling.

Regardless of the research problem you are investigating and the methodology you choose, all research proposals must address the following questions:

  • What do you plan to accomplish? Be clear and succinct in defining the research problem and what it is you are proposing to investigate.
  • Why do you want to do the research? In addition to detailing your research design, you also must conduct a thorough review of the literature and provide convincing evidence that it is a topic worthy of in-depth study. A successful research proposal must answer the "So What?" question.
  • How are you going to conduct the research? Be sure that what you propose is doable. If you're having difficulty formulating a research problem to propose investigating, go here for strategies in developing a problem to study.

Common Mistakes to Avoid

  • Failure to be concise . A research proposal must be focused and not be "all over the map" or diverge into unrelated tangents without a clear sense of purpose.
  • Failure to cite landmark works in your literature review . Proposals should be grounded in foundational research that lays a foundation for understanding the development and scope of the the topic and its relevance.
  • Failure to delimit the contextual scope of your research [e.g., time, place, people, etc.]. As with any research paper, your proposed study must inform the reader how and in what ways the study will frame the problem.
  • Failure to develop a coherent and persuasive argument for the proposed research . This is critical. In many workplace settings, the research proposal is a formal document intended to argue for why a study should be funded.
  • Sloppy or imprecise writing, or poor grammar . Although a research proposal does not represent a completed research study, there is still an expectation that it is well-written and follows the style and rules of good academic writing.
  • Too much detail on minor issues, but not enough detail on major issues . Your proposal should focus on only a few key research questions in order to support the argument that the research needs to be conducted. Minor issues, even if valid, can be mentioned but they should not dominate the overall narrative.

Procter, Margaret. The Academic Proposal.  The Lab Report. University College Writing Centre. University of Toronto; Sanford, Keith. Information for Students: Writing a Research Proposal. Baylor University; Wong, Paul T. P. How to Write a Research Proposal. International Network on Personal Meaning. Trinity Western University; Writing Academic Proposals: Conferences, Articles, and Books. The Writing Lab and The OWL. Purdue University; Writing a Research Proposal. University Library. University of Illinois at Urbana-Champaign.

Structure and Writing Style

Beginning the Proposal Process

As with writing most college-level academic papers, research proposals are generally organized the same way throughout most social science disciplines. The text of proposals generally vary in length between ten and thirty-five pages, followed by the list of references. However, before you begin, read the assignment carefully and, if anything seems unclear, ask your professor whether there are any specific requirements for organizing and writing the proposal.

A good place to begin is to ask yourself a series of questions:

  • What do I want to study?
  • Why is the topic important?
  • How is it significant within the subject areas covered in my class?
  • What problems will it help solve?
  • How does it build upon [and hopefully go beyond] research already conducted on the topic?
  • What exactly should I plan to do, and can I get it done in the time available?

In general, a compelling research proposal should document your knowledge of the topic and demonstrate your enthusiasm for conducting the study. Approach it with the intention of leaving your readers feeling like, "Wow, that's an exciting idea and I can’t wait to see how it turns out!"

Most proposals should include the following sections:

I.  Introduction

In the real world of higher education, a research proposal is most often written by scholars seeking grant funding for a research project or it's the first step in getting approval to write a doctoral dissertation. Even if this is just a course assignment, treat your introduction as the initial pitch of an idea based on a thorough examination of the significance of a research problem. After reading the introduction, your readers should not only have an understanding of what you want to do, but they should also be able to gain a sense of your passion for the topic and to be excited about the study's possible outcomes. Note that most proposals do not include an abstract [summary] before the introduction.

Think about your introduction as a narrative written in two to four paragraphs that succinctly answers the following four questions :

  • What is the central research problem?
  • What is the topic of study related to that research problem?
  • What methods should be used to analyze the research problem?
  • Answer the "So What?" question by explaining why this is important research, what is its significance, and why should someone reading the proposal care about the outcomes of the proposed study?

II.  Background and Significance

This is where you explain the scope and context of your proposal and describe in detail why it's important. It can be melded into your introduction or you can create a separate section to help with the organization and narrative flow of your proposal. Approach writing this section with the thought that you can’t assume your readers will know as much about the research problem as you do. Note that this section is not an essay going over everything you have learned about the topic; instead, you must choose what is most relevant in explaining the aims of your research.

To that end, while there are no prescribed rules for establishing the significance of your proposed study, you should attempt to address some or all of the following:

  • State the research problem and give a more detailed explanation about the purpose of the study than what you stated in the introduction. This is particularly important if the problem is complex or multifaceted .
  • Present the rationale of your proposed study and clearly indicate why it is worth doing; be sure to answer the "So What? question [i.e., why should anyone care?].
  • Describe the major issues or problems examined by your research. This can be in the form of questions to be addressed. Be sure to note how your proposed study builds on previous assumptions about the research problem.
  • Explain the methods you plan to use for conducting your research. Clearly identify the key sources you intend to use and explain how they will contribute to your analysis of the topic.
  • Describe the boundaries of your proposed research in order to provide a clear focus. Where appropriate, state not only what you plan to study, but what aspects of the research problem will be excluded from the study.
  • If necessary, provide definitions of key concepts, theories, or terms.

III.  Literature Review

Connected to the background and significance of your study is a section of your proposal devoted to a more deliberate review and synthesis of prior studies related to the research problem under investigation . The purpose here is to place your project within the larger whole of what is currently being explored, while at the same time, demonstrating to your readers that your work is original and innovative. Think about what questions other researchers have asked, what methodological approaches they have used, and what is your understanding of their findings and, when stated, their recommendations. Also pay attention to any suggestions for further research.

Since a literature review is information dense, it is crucial that this section is intelligently structured to enable a reader to grasp the key arguments underpinning your proposed study in relation to the arguments put forth by other researchers. A good strategy is to break the literature into "conceptual categories" [themes] rather than systematically or chronologically describing groups of materials one at a time. Note that conceptual categories generally reveal themselves after you have read most of the pertinent literature on your topic so adding new categories is an on-going process of discovery as you review more studies. How do you know you've covered the key conceptual categories underlying the research literature? Generally, you can have confidence that all of the significant conceptual categories have been identified if you start to see repetition in the conclusions or recommendations that are being made.

NOTE: Do not shy away from challenging the conclusions made in prior research as a basis for supporting the need for your proposal. Assess what you believe is missing and state how previous research has failed to adequately examine the issue that your study addresses. Highlighting the problematic conclusions strengthens your proposal. For more information on writing literature reviews, GO HERE .

To help frame your proposal's review of prior research, consider the "five C’s" of writing a literature review:

  • Cite , so as to keep the primary focus on the literature pertinent to your research problem.
  • Compare the various arguments, theories, methodologies, and findings expressed in the literature: what do the authors agree on? Who applies similar approaches to analyzing the research problem?
  • Contrast the various arguments, themes, methodologies, approaches, and controversies expressed in the literature: describe what are the major areas of disagreement, controversy, or debate among scholars?
  • Critique the literature: Which arguments are more persuasive, and why? Which approaches, findings, and methodologies seem most reliable, valid, or appropriate, and why? Pay attention to the verbs you use to describe what an author says/does [e.g., asserts, demonstrates, argues, etc.].
  • Connect the literature to your own area of research and investigation: how does your own work draw upon, depart from, synthesize, or add a new perspective to what has been said in the literature?

IV.  Research Design and Methods

This section must be well-written and logically organized because you are not actually doing the research, yet, your reader must have confidence that you have a plan worth pursuing . The reader will never have a study outcome from which to evaluate whether your methodological choices were the correct ones. Thus, the objective here is to convince the reader that your overall research design and proposed methods of analysis will correctly address the problem and that the methods will provide the means to effectively interpret the potential results. Your design and methods should be unmistakably tied to the specific aims of your study.

Describe the overall research design by building upon and drawing examples from your review of the literature. Consider not only methods that other researchers have used, but methods of data gathering that have not been used but perhaps could be. Be specific about the methodological approaches you plan to undertake to obtain information, the techniques you would use to analyze the data, and the tests of external validity to which you commit yourself [i.e., the trustworthiness by which you can generalize from your study to other people, places, events, and/or periods of time].

When describing the methods you will use, be sure to cover the following:

  • Specify the research process you will undertake and the way you will interpret the results obtained in relation to the research problem. Don't just describe what you intend to achieve from applying the methods you choose, but state how you will spend your time while applying these methods [e.g., coding text from interviews to find statements about the need to change school curriculum; running a regression to determine if there is a relationship between campaign advertising on social media sites and election outcomes in Europe ].
  • Keep in mind that the methodology is not just a list of tasks; it is a deliberate argument as to why techniques for gathering information add up to the best way to investigate the research problem. This is an important point because the mere listing of tasks to be performed does not demonstrate that, collectively, they effectively address the research problem. Be sure you clearly explain this.
  • Anticipate and acknowledge any potential barriers and pitfalls in carrying out your research design and explain how you plan to address them. No method applied to research in the social and behavioral sciences is perfect, so you need to describe where you believe challenges may exist in obtaining data or accessing information. It's always better to acknowledge this than to have it brought up by your professor!

V.  Preliminary Suppositions and Implications

Just because you don't have to actually conduct the study and analyze the results, doesn't mean you can skip talking about the analytical process and potential implications . The purpose of this section is to argue how and in what ways you believe your research will refine, revise, or extend existing knowledge in the subject area under investigation. Depending on the aims and objectives of your study, describe how the anticipated results will impact future scholarly research, theory, practice, forms of interventions, or policy making. Note that such discussions may have either substantive [a potential new policy], theoretical [a potential new understanding], or methodological [a potential new way of analyzing] significance.   When thinking about the potential implications of your study, ask the following questions:

  • What might the results mean in regards to challenging the theoretical framework and underlying assumptions that support the study?
  • What suggestions for subsequent research could arise from the potential outcomes of the study?
  • What will the results mean to practitioners in the natural settings of their workplace, organization, or community?
  • Will the results influence programs, methods, and/or forms of intervention?
  • How might the results contribute to the solution of social, economic, or other types of problems?
  • Will the results influence policy decisions?
  • In what way do individuals or groups benefit should your study be pursued?
  • What will be improved or changed as a result of the proposed research?
  • How will the results of the study be implemented and what innovations or transformative insights could emerge from the process of implementation?

NOTE:   This section should not delve into idle speculation, opinion, or be formulated on the basis of unclear evidence . The purpose is to reflect upon gaps or understudied areas of the current literature and describe how your proposed research contributes to a new understanding of the research problem should the study be implemented as designed.

ANOTHER NOTE : This section is also where you describe any potential limitations to your proposed study. While it is impossible to highlight all potential limitations because the study has yet to be conducted, you still must tell the reader where and in what form impediments may arise and how you plan to address them.

VI.  Conclusion

The conclusion reiterates the importance or significance of your proposal and provides a brief summary of the entire study . This section should be only one or two paragraphs long, emphasizing why the research problem is worth investigating, why your research study is unique, and how it should advance existing knowledge.

Someone reading this section should come away with an understanding of:

  • Why the study should be done;
  • The specific purpose of the study and the research questions it attempts to answer;
  • The decision for why the research design and methods used where chosen over other options;
  • The potential implications emerging from your proposed study of the research problem; and
  • A sense of how your study fits within the broader scholarship about the research problem.

VII.  Citations

As with any scholarly research paper, you must cite the sources you used . In a standard research proposal, this section can take two forms, so consult with your professor about which one is preferred.

  • References -- a list of only the sources you actually used in creating your proposal.
  • Bibliography -- a list of everything you used in creating your proposal, along with additional citations to any key sources relevant to understanding the research problem.

In either case, this section should testify to the fact that you did enough preparatory work to ensure the project will complement and not just duplicate the efforts of other researchers. It demonstrates to the reader that you have a thorough understanding of prior research on the topic.

Most proposal formats have you start a new page and use the heading "References" or "Bibliography" centered at the top of the page. Cited works should always use a standard format that follows the writing style advised by the discipline of your course [e.g., education=APA; history=Chicago] or that is preferred by your professor. This section normally does not count towards the total page length of your research proposal.

Develop a Research Proposal: Writing the Proposal. Office of Library Information Services. Baltimore County Public Schools; Heath, M. Teresa Pereira and Caroline Tynan. “Crafting a Research Proposal.” The Marketing Review 10 (Summer 2010): 147-168; Jones, Mark. “Writing a Research Proposal.” In MasterClass in Geography Education: Transforming Teaching and Learning . Graham Butt, editor. (New York: Bloomsbury Academic, 2015), pp. 113-127; Juni, Muhamad Hanafiah. “Writing a Research Proposal.” International Journal of Public Health and Clinical Sciences 1 (September/October 2014): 229-240; Krathwohl, David R. How to Prepare a Dissertation Proposal: Suggestions for Students in Education and the Social and Behavioral Sciences . Syracuse, NY: Syracuse University Press, 2005; Procter, Margaret. The Academic Proposal. The Lab Report. University College Writing Centre. University of Toronto; Punch, Keith and Wayne McGowan. "Developing and Writing a Research Proposal." In From Postgraduate to Social Scientist: A Guide to Key Skills . Nigel Gilbert, ed. (Thousand Oaks, CA: Sage, 2006), 59-81; Wong, Paul T. P. How to Write a Research Proposal. International Network on Personal Meaning. Trinity Western University; Writing Academic Proposals: Conferences , Articles, and Books. The Writing Lab and The OWL. Purdue University; Writing a Research Proposal. University Library. University of Illinois at Urbana-Champaign.

  • << Previous: Writing a Reflective Paper
  • Next: Generative AI and Writing >>
  • Last Updated: May 7, 2024 9:45 AM
  • URL: https://libguides.usc.edu/writingguide/assignments

Writing the Data Analysis Plan

  • First Online: 01 January 2010

Cite this chapter

how to make data analysis in research proposal

  • A. T. Panter 4  

5790 Accesses

3 Altmetric

You and your project statistician have one major goal for your data analysis plan: You need to convince all the reviewers reading your proposal that you would know what to do with your data once your project is funded and your data are in hand. The data analytic plan is a signal to the reviewers about your ability to score, describe, and thoughtfully synthesize a large number of variables into appropriately-selected quantitative models once the data are collected. Reviewers respond very well to plans with a clear elucidation of the data analysis steps – in an appropriate order, with an appropriate level of detail and reference to relevant literatures, and with statistical models and methods for that map well into your proposed aims. A successful data analysis plan produces reviews that either include no comments about the data analysis plan or better yet, compliments it for being comprehensive and logical given your aims. This chapter offers practical advice about developing and writing a compelling, “bullet-proof” data analytic plan for your grant application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
  • Available as EPUB and PDF
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Aiken, L. S. & West, S. G. (1991). Multiple regression: testing and interpreting interactions . Newbury Park, CA: Sage.

Google Scholar  

Aiken, L. S., West, S. G., & Millsap, R. E. (2008). Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest and Reno’s (1990) survey of PhD programs in North America. American Psychologist , 63 , 32–50.

Article   PubMed   Google Scholar  

Allison, P. D. (2003). Missing data techniques for structural equation modeling. Journal of Abnormal Psychology , 112 , 545–557.

American Psychological Association (APA) Task Force to Increase the Quantitative Pipeline (2009). Report of the task force to increase the quantitative pipeline . Washington, DC: American Psychological Association.

Bauer, D. & Curran, P. J. (2004). The integration of continuous and discrete latent variables: Potential problems and promising opportunities. Psychological Methods , 9 , 3–29.

Bollen, K. A. (1989). Structural equations with latent variables . New York: Wiley.

Bollen, K. A. & Curran, P. J. (2007). Latent curve models: A structural equation modeling approach . New York: Wiley.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Multiple correlation/regression for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.

Curran, P. J., Bauer, D. J., & Willoughby, M. T. (2004). Testing main effects and interactions in hierarchical linear growth models. Psychological Methods , 9 , 220–237.

Embretson, S. E. & Reise, S. P. (2000). Item response theory for psychologists . Mahwah, NJ: Erlbaum.

Enders, C. K. (2006). Analyzing structural equation models with missing data. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (pp. 313–342). Greenwich, CT: Information Age.

Hosmer, D. & Lemeshow, S. (1989). Applied logistic regression . New York: Wiley.

Hoyle, R. H. & Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 158–176). Thousand Oaks: Sage.

Kaplan, D. & Elliott, P. R. (1997). A didactic example of multilevel structural equation modeling applicable to the study of organizations. Structural Equation Modeling , 4 , 1–23.

Article   Google Scholar  

Lanza, S. T., Collins, L. M., Schafer, J. L., & Flaherty, B. P. (2005). Using data augmentation to obtain standard errors and conduct hypothesis tests in latent class and latent transition analysis. Psychological Methods , 10 , 84–100.

MacKinnon, D. P. (2008). Introduction to statistical mediation analysis . Mahwah, NJ: Erlbaum.

Maxwell, S. E. (2004). The persistence of underpowered studies in psychological research: Causes, consequences, and remedies. Psychological Methods , 9 , 147–163.

McCullagh, P. & Nelder, J. (1989). Generalized linear models . London: Chapman and Hall.

McDonald, R. P. & Ho, M. R. (2002). Principles and practices in reporting structural equation modeling analyses. Psychological Methods , 7 , 64–82.

Messick, S. (1989). Validity. In R. L. Linn (Ed.), Educational measurement (3rd ed., pp. 13–103). New York: Macmillan.

Muthén, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research , 22 , 376–398.

Muthén, B. (2008). Latent variable hybrids: overview of old and new models. In G. R. Hancock & K. M. Samuelsen (Eds.), Advances in latent variable mixture models (pp. 1–24). Charlotte, NC: Information Age.

Muthén, B. & Masyn, K. (2004). Discrete-time survival mixture analysis. Journal of Educational and Behavioral Statistics , 30 , 27–58.

Muthén, L. K. & Muthén, B. O. (2004). Mplus, statistical analysis with latent variables: User’s guide . Los Angeles, CA: Muthén &Muthén.

Peugh, J. L. & Enders, C. K. (2004). Missing data in educational research: a review of reporting practices and suggestions for improvement. Review of Educational Research , 74 , 525–556.

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics , 31 , 437–448.

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2003, September). Probing interactions in multiple linear regression, latent curve analysis, and hierarchical linear modeling: Interactive calculation tools for establishing simple intercepts, simple slopes, and regions of significance [Computer software]. Available from http://www.quantpsy.org .

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research , 42 , 185–227.

Raudenbush, S. W. & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.

Radloff, L. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement , 1 , 385–401.

Rosenberg, M. (1965). Society and the adolescent self-image . Princeton, NJ: Princeton University Press.

Schafer. J. L. & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods , 7 , 147–177.

Schumacker, R. E. (2002). Latent variable interaction modeling. Structural Equation Modeling , 9 , 40–54.

Schumacker, R. E. & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling . Mahwah, NJ: Erlbaum.

Selig, J. P. & Preacher, K. J. (2008, June). Monte Carlo method for assessing mediation: An interactive tool for creating confidence intervals for indirect effects [Computer software]. Available from http://www.quantpsy.org .

Singer, J. D. & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events. Psychological Bulletin , 110 , 268–290.

Singer, J. D. & Willett, J. B. (1993). It’s about time: Using discrete-time survival analysis to study duration and the timing of events. Journal of Educational Statistics , 18 , 155–195.

Singer, J. D. & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence . New York: Oxford University.

Book   Google Scholar  

Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods , 3 , 4–69.

Wirth, R. J. & Edwards, M. C. (2007). Item factor analysis: Current approaches and future directions. Psychological Methods , 12 , 58–79.

Article   PubMed   CAS   Google Scholar  

Download references

Author information

Authors and affiliations.

L. L. Thurstone Psychometric Laboratory, Department of Psychology, University of North Carolina, Chapel Hill, NC, USA

A. T. Panter

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to A. T. Panter .

Editor information

Editors and affiliations.

National Institute of Mental Health, Executive Blvd. 6001, Bethesda, 20892-9641, Maryland, USA

Willo Pequegnat

Ellen Stover

Delafield Place, N.W. 1413, Washington, 20011, District of Columbia, USA

Cheryl Anne Boyce

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media, LLC

About this chapter

Panter, A.T. (2010). Writing the Data Analysis Plan. In: Pequegnat, W., Stover, E., Boyce, C. (eds) How to Write a Successful Research Grant Application. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1454-5_22

Download citation

DOI : https://doi.org/10.1007/978-1-4419-1454-5_22

Published : 20 August 2010

Publisher Name : Springer, Boston, MA

Print ISBN : 978-1-4419-1453-8

Online ISBN : 978-1-4419-1454-5

eBook Packages : Medicine Medicine (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Publish with us

Policies and ethics

  • Find a journal
  • Track your research

COMMENTS

  1. 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".

  2. Data Analysis in Research: Types & Methods

    Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. Three essential things occur during the data ...

  3. Data Analytics Resources: Writing a Research Proposal

    Show that you understand the current state of research on your topic. Approach: Make a case for your methodology. Demonstrate that you have carefully considered the data, tools, and procedures necessary to conduct your research: Achievability: Confirm that your project is feasible within the timeline of your program or funding deadline

  4. How to Create a Data Analysis Plan: A Detailed Guide

    In this blog article, we will explore how to create a data analysis plan: the content and structure. This data analysis plan serves as a roadmap to how data collected will be organised and analysed. It includes the following aspects: Clearly states the research objectives and hypothesis. Identifies the dataset to be used.

  5. Data Analysis in Quantitative Research Proposal

    Data Analysis is to make general conclusions (conclusions), make a prediction (prediction), or make an estimate (estimation). This entry was posted in English Articles. Bookmark the permalink. Data analysis in quantitative research proposal is one part of the chapter that researchers need in the beginning of writing a research proposal.

  6. 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.

  7. Top 10 Data Analysis Research Proposal Templates with ...

    Template 1: Data Analysis in Research Proposal. Click Here to Download. Introducing this cover slide of the proposal that has been professionally designed and sets the stage for your entire research proposal. With ample space for an image, it captures your audience's attention from the start. Your proposal's credentials, both for the recipient ...

  8. Research Design

    Your data analysis methods; A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data. You might have to write up a research design as a standalone assignment, or it might be part of a larger research proposal or other project. In either case, you should ...

  9. How to Write a Research Proposal: A Step-by-Step

    Writing a research proposal in structured steps ensures a comprehensive and coherent presentation of your research project. Let's look at the explanation for each of the steps here: Step 1: Title and Abstract. Step 2: Introduction. Step 3: Research objectives. Step 4: Literature review.

  10. What Is A Research Proposal? Examples + Template

    The purpose of the research proposal (its job, so to speak) is to convince your research supervisor, committee or university that your research is suitable (for the requirements of the degree program) and manageable (given the time and resource constraints you will face). The most important word here is "convince" - in other words, your ...

  11. PDF Developing a Quantitative Data Analysis Plan

    A Data Analysis Plan (DAP) is about putting thoughts into a plan of action. Research questions are often framed broadly and need to be clarified and funnelled down into testable hypotheses and action steps. The DAP provides an opportunity for input from collaborators and provides a platform for training. Having a clear plan of action is also ...

  12. 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.

  13. Creating a Data Analysis Plan: What to Consider When Choosing

    The first step in a data analysis plan is to describe the data collected in the study. This can be done using figures to give a visual presentation of the data and statistics to generate numeric descriptions of the data. Selection of an appropriate figure to represent a particular set of data depends on the measurement level of the variable.

  14. 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'.

  15. Writing a Research Proposal

    The design elements and procedures for conducting research are governed by standards of the predominant discipline in which the problem resides, therefore, the guidelines for research proposals are more exacting and less formal than a general project proposal. Research proposals contain extensive literature reviews.

  16. Writing the Data Analysis Plan

    22.1 Writing the Data Analysis Plan. Congratulations! You have now arrived at one of the most creative and straightforward, sections of your grant proposal. You and your project statistician have one major goal for your data analysis plan: You need to convince all the reviewers reading your proposal that you would know what to do with your data ...

  17. Data Analysis Plan: Examples & Templates

    A data analysis plan is a roadmap for how you're going to organize and analyze your survey data—and it should help you achieve three objectives that relate to the goal you set before you started your survey: Answer your top research questions. Use more specific survey questions to understand those answers. Segment survey respondents to ...

  18. What Is a Research Methodology?

    Step 1: Explain your methodological approach. Step 2: Describe your data collection methods. Step 3: Describe your analysis method. Step 4: Evaluate and justify the methodological choices you made. Tips for writing a strong methodology chapter. Other interesting articles.

  19. PDF Writing a qualitative research proposal

    2. Make sure you cannot get data from a repository such as Qualidata instead. It is not ethical to do primary research if you can answer your research question using a secondary analysis of existing data for which you have sufficient contextual information about the population the data come from, the way the data were collected, and who by. 3.

  20. Writing a Research Proposal

    This video was recorded for a third year Midwifery module. Featuring University of Nottingham Division of Midwifery's Zoey Spendlove, filmed by the Health E-...

  21. PDF WRITING AN EFFECTIVE RESEARCH PROPOSAL

    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.

  22. PDF Research Proposal for Retrospective Data Analysis

    research uses of identifiable private information or identifiable biospecimens, if at least one of the following criteria is met: (i) The identifiable private information or identifiable biospecimens are publicly available 4.ii. Secondary Research Use of Identifiable Private Information and