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Choosing the Right Research Methodology: A Guide for Researchers

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Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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What Is Research Methodology?

I f you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

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We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

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MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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How to Choose the Right Research Methodology

If you’re struggling with how to choose research methodology for your study, you are not alone. A wrongly chosen research methodology impacts the quality and success of a research study, which makes it critical to know how to choose the right research methodology. Early career researchers are often confused over the choice of correct study research methods that will help them accomplish the goals of their study. So, what is methodology in research papers? How to select research methodology that works? First of all, even before thinking about how to choose research methods, a researcher must pose the right research question/hypothesis or a well-defined problem statement.

In general, when asking yourself ‘how to choose the right research methodology’ be sure to consider the following essentials. A good study research method must

• Align with the intended scope of research and its objectives
• Allow completion of the research project within the stipulated time and with available resources
• Align with the norms of the specific research area
• Include appropriate data-collection tools
• Include data-analysis strategies compatible with the dataset
• Include an appropriate sampling design that takes into account access to the target group/population

Table of Contents

Types of Research Methodology

If you’re considering how to choose research methods, you need to understand the types of research methodology. Here’s an overview of the types of research methodology, with examples, you must know when you’re confused about how to choose a methodology for research.

• Research on identifying consumer preferences for types of face mask is an example of  descriptive research . In this type of research, a researcher simply reports the present state of affairs and has no control over the variables. It’s not difficult to decide how to choose the right research methodology for descriptive studies; most researchers use surveys as data-collection tools.
• Research on the possible future emergence of new SARS-CoV-2 variants is  analytical research.  In this type, researchers study existing data on the origin of the variants. The study research method must consider data sourcing and data-mining tools, comparative and correlational assessments, and predictive modelling approaches.
• Studies in fields such as space sciences, ecology, and archaeology are examples of  fundamental research . There is no single answer to how to select a research method here as these are aimed at creating a broad knowledge base to be utilized in future for other types of research.
• The testing of antiviral drugs, analysis of political trends (polls), and the mapping of market trends (e.g., use of cryptocurrency) fall in the domain of  applied research.  These are aimed at finding solutions for problems or enabling the planning of outcomes for a business or political agenda so, if you’re wondering how to choose the right research methodology, make sure it reflects this.
• A meteorologist gathers quantitative measurements of variables that influence weather. Such research is  quantitative research  and is characterized by the use of rigorous statistical methods, with outcomes presented in the form of graphs and tables.
• Studies on peoples’ ideas and opinions on social, political, or economic issues is  qualitative research.  It is exploratory in nature, and data are collected through interviews.
• Research aimed at developing hypotheses and theories or reinterpreting abstract concepts is called  conceptual research,  for example, a review of Einstein’s theory of relativity after the discovery of gravitational waves.
• Testing of a hypothesis falls in the category of  empirical research —which involves experiments to gather evidence to either prove or disprove the hypothesis. The experimental results of empirical research are fact-based, reliable, and reproducible.

Now that you’ve understood the types of research, it’s time to decide how to choose the research methodology for your work. Keep in mind that the type of research you are conducting should be matched with the three broad  categories of study research methods .

1. Quantitative methods test hypotheses or problem statements and involve:

• Close-ended and structured data collection
• Large sample sizes
• Deductive reasoning and objective approaches

Common study research methods under this are:

• Laboratory experiments.  These are conducted in controlled environments by manipulating variables to collect numerical data.
• Meta-analysis.  This is a statistical method used to deduce a universal conclusion from multiple scientific studies trying to answer the same question. It minimizes disparities across studies owing to differences in sampling strategies and other variables.
• Select a sample representative of the target population
• Pre-test the survey on a small number of people before rolling it out on a large scale
• Adopt robust data-entry approaches such as a two-pass verification to avoid errors and discrepancies
• Design a survey from scratch or use publicly available survey data
• Secondary data collection.  This study research method uses existing data from government reports, press releases, corporate reports, etc. to add significance to the primary research.

2. Qualitative methods explore intangible occurrences and are used to form themes or develop theories or concepts. These involve:

• Smaller samples
• Mostly semi-structured data collection
• Inductive reasoning and subjective and open-ended approaches

Most widely adopted study research methods under this are

• Interviews.  Researchers ask open-ended questions to participants and collect qualitative data.
• Facilitate or prompt a thematic discussion among a group of people
• Collect opinions and thoughts via recordings and prepare transcripts
• Segregate information into sets and subsets
• Analyze information and interpret conclusions, themes, or patterns
• Case studies.  These are used to study a phenomenon using multiple data sources and uncover all of its facets to fine precision.
• Collect authentic information
• Discover research methodology suited to their research
• Find data-collection approaches
• Interpret their results in light of related research

3. Combination or mixed study research methods are used in studies where one approach may not suffice for obtaining in-depth and comprehensive understanding of the research problem. In these cases, researchers often adopt mixed study research methods. A combination of both qualitative and quantitative study research methods enhances the overall strength of research outcomes.

There isn’t a one-size-fits-all answer to how to choose the right research methodology. While the quantitative approach is commonly believed to be the strongest study research method, but this may not always be so. In certain scenarios, numbers may lead to oversimplified conclusions and compromise in-depth contextualized understanding. Some believe that mixed research methodology is most powerful; however, it may not be applicable across all settings and is restricted by time and resource limitations. Thus, the final decision of how to select research methodology must match the research objectives and proposed outcomes.

R Discovery as a useful tool in choosing study research methods

R Discovery , is an   AI-powered mobile app designed to help researchers find all the recent and relevant literature they need at different stages of research, particularly when they are framing their research questions and thinking of how to choose the right research methodology to answer them.

What R Discovery does:

• Finds and delivers top three articles most relevant to a researcher based on their topic preferences every day, so that they don’t miss out on any important literature
• Saves reading time by providing easy-to-follow summaries of research papers
• Allows researchers to access full texts through their institutional credentials

Suggested readings for how to choose research methods

• https://www.thestudyspace.com/page/choosing-appropriate-research-methodologies/
• https://doi.org/10.1016/j.jbusres.2019.07.039 .
• https://bookdown.org/ejvanholm/Textbook/types-of-research.html
• Rebolj, A. Biba. (2013). The case study as a type of qualitative research. Journal of Contemporary Educational Studies. 28–43.
• Mishra, Dr. Shanti Bhushan & Alok, Dr. Shashi. (2017). Handbook of research methodology.

Frequently Asked Questions (FAQs) on research methodology  

Q: What is research methodology ?  

Research methodology refers to the systematic and structured approach used to conduct research. It encompasses the overall framework, strategies, and techniques employed to gather data, analyze information, and draw conclusions. Research methodology guides researchers in designing and executing their studies, ensuring that the research process is rigorous, logical, and aligned with the research objectives.  

Q: What is the purpose of research methodology ?  

The purpose of research methodology is to provide researchers with a systematic and structured approach to conducting research. It ensures that researchers maintain a high level of rigor and quality in their studies, guides decision-making, and enhances research efficiency by providing a clear roadmap for conducting the study. It is also a great way of validating research findings.  

Q: Why is research methodology important for research?  

One cannot deny the role and importance of research methodology in conducting high-quality and reliable research. It provides researchers with a systematic and structured framework that ensures the research study is well-planned, properly executed, and yields valid and trustworthy results.  

Q: What is the difference between research methodology and research methods ?  

Research methodology refers to the overarching approach and framework used to conduct research, including the theoretical and philosophical underpinnings of the study. It addresses questions such as the research design, data collection methods, sampling techniques, and data analysis procedures. Research methods refer to the specific techniques, tools, and procedures employed within the research methodology to gather and analyze data. Research methods can include qualitative or quantitative approaches, surveys, interviews, experiments, or case studies.  

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

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Research Project Guide

Research Methodology Types + How To Choose The Right One

Explore various research methodology types and discover how to choose the right one for your project with our comprehensive guide.

Oct 27, 2024

Starting a research project can feel like wandering through a maze without a map( how to start a research project ). You know the destination—an insightful, well-supported paper—but getting there can be daunting. That's where understanding research methodology types shines. Choosing the correct method is crucial for conducting efficient, meaningful research. This guide will help you through various methodologies, helping you conduct research quickly and write more effectively. When you’re ready to streamline your project further, Otio’s AI research and writing partner can be your trusted sidekick, making your research process and writing sharper.

Table Of Contents

What is research methodology.

9 Tips On How To Conduct Academic Research

Sampling In Research

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Research methodology is your blueprint for how to tackle a research project. It’s about planning and detailing how you will answer your research questions. This plan needs to be logical and systematic so you can trust the results you get. Consider it your guide to collecting, analyzing, and interpreting data.

Why Choose the Right Methodology?

Choosing the correct research methodology is crucial. It allows other researchers to replicate your work and verify your results. With transparent methods, you can also easily explain your research choices to others. This framework helps you define your questions, hypotheses, and objectives while ensuring your findings are valid and reliable. It’s also about being efficient with time and resources, following ethical guidelines, and minimizing bias and errors.

Exploring Research Methodology Types

Understanding research methodology is crucial for any research endeavor. Here’s a breakdown of the primary types

1. Qualitative Research  

Qualitative research captures and analyzes textual data, focusing on interviews, observations, and focus groups. It's exploratory and subjective, often aiming to understand perceptions or experiences. While it's time-consuming, it offers deep insights. However, bias and privacy concerns can be drawbacks.

2. Quantitative Research  

Quantitative research is all about numbers, using surveys, tests, and databases to gather data from large samples. Thanks to software analysis, it's objective and efficient. It’s ideal for testing hypotheses or measuring relationships. However, it can be costly and might not reflect real-life behaviors.

3. Mixed-Method Research  

A mixed-method approach blends qualitative and quantitative research, providing a fuller picture with both data and human perspectives. This method is ideal for comprehensive studies.

Tips for Choosing the Right Methodology

Choosing the proper methodology starts with a clear objective. Ensure your research question is specific, applicable, and valuable. Your study should represent your target population accurately, with inclusive surveys and questions that address your research goals. Consider your time constraints. If time is tight, prioritize faster data collection methods.

Meet Otio, Your Ultimate Research Sidekick

Knowledge workers, researchers, and students need help with content overload, often relying on fragmented tools. Otio offers a solution with a unified workspace. As your AI research and writing partner , Otio helps you collect and extract critical information efficiently, moving you from a reading list to a first draft faster. Try Otio for free today !

Related Reading

• How to Find Academic Sources • How to Analyze Quantitative Data • Can Ai Write a Paper for Me • How Long Does It Take to Write a Research Paper • How to Create a Research Question • How to Organize a Research Paper • Argumentative Essay Topics • Methods Section of Research Paper​

9 Tips on How to Conduct Academic Research

1. Equip the Potential of Otio for Research

Knowledge workers, researchers, and students face content overload in today's world. The challenge is real: dealing with fragmented, complex, and manual tools. Many end up piecing together cumbersome bookmarking, read-it-later, and note-taking apps. Otio tackles this head-on by offering an AI-native workspace for researchers . It helps you collect diverse data sources, from bookmarks and tweets to YouTube videos and full-length books. You can extract critical insights with detailed AI-generated notes and source-grounded Q&A chat. 

Finally, create draft outputs with the resources you've gathered. Otio accelerates your journey from the reading list to the first draft. Plus, with features like AI-assisted writing and the ability to chat with individual links or entire knowledge bases, research and writing become much quicker. Try Otio for free today , and let it be your AI partner.

2. Choose and Refine Your Research Topic

Picking a research topic can be daunting. It's the first step in writing a paper and needs to be correct. Start by selecting a topic within the bounds of your assignment. Your instructor often provides guidelines to follow. Straying from them can result in your proposal being rejected. Select a topic that interests you personally. Researching and writing about something you care about is more enjoyable. Also, choose a subject with a manageable amount of information. 

Do a preliminary search to find enough sources to meet your needs. Too much information means you may need to narrow your topic, while too little requires broadening it. Be original to stand out. Instructors read countless papers on the same issues. Choose something interesting and off the beaten path. If you still need help, ask your instructor for assistance. Once you've identified your topic, pose it as a question. For instance, if you're interested in obesity in America, ask, "What are the causes of obesity in America?" This helps you identify key concepts or keywords for your research.

3. Conduct a Preliminary Information Search

Before diving into your research , perform a preliminary search to see if there's enough information for your needs and to set the context. Use library reference materials like encyclopedias and dictionaries, books, periodical databases, and Internet search engines. Your lecture notes, textbooks, and reserve readings can also provide background information. Be prepared to adjust your topic focus based on available resources.

4. Find and Gather Your Research Materials

Now that your research direction is clear start locating materials for your topic. Search for books using One Search. Try a keyword search if a subject search doesn't yield enough results. Record the citation information (author, title, etc.) and location (call number and collection) of items. When you find a book, check nearby shelves for similar items. 

The Aleph catalog also indexes audio-visual holdings. Use the library's electronic periodical databases for magazine and newspaper articles. Choose the databases and formats best suited to your topic. Ask a librarian if you need help finding the correct database. Use search engines and subject directories to find Internet materials. Check the Internet Resources section of your library's website for helpful subject links.

5. Evaluate the Quality of Your Sources

Use the CARS Checklist for Information Quality to assess the authority and quality of information you've found. Your instructor expects credible, reliable information, and you should, too. This is especially important for unreliable Internet resources.

6. Take Detailed Notes

Consult your chosen resources and note valuable information for your paper. Document all sources, even if you might not use them. You'll need the author, title, publisher, URL, and other details later for your bibliography.

7. Organize and Write Your Paper

Start by organizing the information you've collected. Create a rough draft to get your ideas on paper in an unfinished form. This helps you organize your ideas and decide on the structure of your final paper. Revise the draft as needed to produce a final product to submit.

8. Properly Cite Your Sources

Give credit where it's due by citing your sources. Citing or documenting sources serves two purposes: giving credit to authors and allowing readers to locate your references. MLA and APA styles are popular citation formats. Failure to cite sources is plagiarism, which is avoidable.

9. Proofread Your Final Draft

The final step is proofreading your paper. Check for spelling, grammar, and punctuation errors. Ensure your sources are cited correctly. Make sure your intended message is clear to the reader.

Selecting a Representative Sample: The Key to Accurate Research

When researching a group, you can only sometimes gather data from everyone. Instead, you choose a sample. This is the subset of individuals who will take part in your study. To ensure your findings are valid, you must carefully select a sample representing the entire group. This process is called a sampling method . Two main types of sampling methods exist: probability and non-probability sampling. 

Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group. Non-probability sampling involves non-random selection based on convenience or other criteria, making it easy to collect data. In your paper or thesis, you should clearly explain how you selected your sample and minimize research bias.

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From Reading List to First Draft: Otio Speeds You Up

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• 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.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 11 November 2024, from https://www.scribbr.co.uk/research-methods/research-design/

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