methods used in research study

15 Types of Research Methods

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Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

• Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
• Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

• Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
• Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

• Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
• Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Example of Ethnography

Liquidated: An Ethnography of Wall Street  by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Example of Phenomenological Research

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Example of Content Analysis

How is Islam Portrayed in Western Media?  by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory  during and after  data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Grounded Theory Example

Developing a Leadership Identity   by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing   by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

With multiple data points collected over extended periods, it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes a detailed analysis of change possible.

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

This approach provides a fast and easy way to make initial hypotheses based on either positive or  negative correlation trends  that can be observed within dataset.

While correlational research can reveal relationships between variables, it cannot establish causality.

Methods used for data analysis may include statistical correlations such as Pearson’s or Spearman’s.

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research design is the framework or blueprint that guides the collection, measurement, and analysis of data in a study. It provides a structured approach to answering research questions, ensuring that the study’s goals are met in an organized, reliable, and valid manner. Research design is crucial as it directly impacts the study’s quality, credibility, and findings.

Research Design

Research design is a systematic plan outlining how a study is conducted, including methods of data collection, procedures, and tools for analysis. It aligns the research question with the appropriate methods, ensuring that the study remains focused, feasible, and ethically sound.

Purpose of Research Design :

• Provides a structured approach for data collection and analysis.
• Ensures consistency in the research process.
• Enhances the reliability and validity of findings.
• Minimizes bias by defining clear procedures and controls.

Types of Research Design

Research designs are typically classified into three main types: qualitative , quantitative , and mixed methods . Each type serves different purposes and is selected based on the nature of the research question, objectives, and resources.

1. Qualitative Research Design

• Definition : Qualitative research focuses on exploring complex phenomena, understanding individual experiences, and generating insights into social or human behavior. It often involves non-numerical data, such as interviews, observations, and textual analysis.
• Case Study : In-depth analysis of a specific individual, group, or event.
• Ethnography : Study of cultural groups and practices within their natural setting.
• Grounded Theory : Development of a theory based on observed data.
• Phenomenology : Exploration of lived experiences and perceptions.
• Example : A case study on how remote work impacts employee well-being by conducting interviews with employees from various industries to gather personal insights and themes.

2. Quantitative Research Design

• Definition : Quantitative research is focused on quantifying variables and using statistical analysis to test hypotheses. It often involves large samples, standardized data collection tools, and numerical data.
• Descriptive : Provides a summary of characteristics or behaviors within a population (e.g., surveys, cross-sectional studies).
• Correlational : Examines relationships between two or more variables without manipulating them.
• Experimental : Involves manipulation of variables to establish cause-and-effect relationships.
• Quasi-Experimental : Similar to experimental design but lacks random assignment.
• Example : An experimental study investigating the effect of a new teaching method on student test scores, with one group using the new method and a control group using traditional methods.

3. Mixed-Methods Research Design

• Definition : Mixed-methods design combines both qualitative and quantitative approaches in a single study, providing a more comprehensive analysis of the research question.
• Explanatory Sequential Design : Quantitative data is collected and analyzed first, followed by qualitative data to explain or expand on the quantitative findings.
• Exploratory Sequential Design : Qualitative data is collected first to explore a phenomenon, followed by quantitative data to confirm or generalize findings.
• Convergent Design : Both qualitative and quantitative data are collected simultaneously and compared to produce integrated insights.
• Example : A study on customer satisfaction, first surveying customers to get quantitative data and then conducting follow-up interviews to explore specific customer feedback in detail.

Methods in Research Design

Various methods are used within research designs to collect and analyze data. Each method is selected based on the research question, data type, and study objectives.

1. Survey and Questionnaire

• Definition : Surveys and questionnaires are tools for collecting standardized data from large samples. They are often used in descriptive and correlational studies.
• Develop questions related to the research objectives.
• Distribute to participants via online platforms, paper forms, or face-to-face interviews.
• Analyze results using statistical software for quantitative insights.
• Example : A survey assessing consumer satisfaction with a new product by collecting data on factors such as ease of use, design, and performance.

2. Interview

• Definition : Interviews are qualitative methods that gather in-depth information through direct questioning. They can be structured, semi-structured, or unstructured.
• Design interview questions that align with the research goals.
• Conduct interviews in person, via phone, or virtually, recording responses for analysis.
• Use thematic or content analysis to interpret findings.
• Example : Conducting semi-structured interviews with educators to explore their experiences with online teaching during the COVID-19 pandemic.

3. Observation

• Definition : Observation involves recording behaviors, actions, or events as they occur naturally. It is often used in ethnographic and case study designs.
• Choose between participant (researcher actively engages) or non-participant observation.
• Develop an observation checklist or guide for consistency.
• Record findings, often through field notes or video, and analyze for patterns.
• Example : Observing interactions in a classroom setting to study student engagement with different teaching methods.

4. Experiment

• Definition : Experiments involve manipulating variables to examine cause-and-effect relationships. They are commonly used in scientific and clinical research.
• Randomly assign participants to control and experimental groups.
• Manipulate the independent variable and measure changes in the dependent variable.
• Use statistical analysis to interpret results.
• Example : A laboratory experiment testing the effectiveness of a new drug on blood pressure by comparing outcomes in treated and untreated groups.

5. Case Study

• Definition : A case study is an in-depth investigation of an individual, group, organization, or event to explore underlying principles and patterns.
• Select a case that represents the phenomenon of interest.
• Use various data sources, including interviews, documents, and observations.
• Analyze for unique insights and apply findings to broader contexts.
• Example : A case study on the strategies a small business used to survive during an economic recession.

Examples of Research Design Applications

• Design : Quantitative, using a survey.
• Goal : To understand consumer preferences for eco-friendly packaging.
• Method : Survey distributed to a random sample of consumers asking about purchasing behaviors and attitudes toward sustainability.
• Design : Experimental, quantitative.
• Goal : To study the effect of sleep deprivation on cognitive performance.
• Method : Participants are randomly assigned to sleep-deprived and control groups, with cognitive performance measured using standardized tests.
• Design : Convergent mixed-methods.
• Goal : To evaluate the effectiveness of a new curriculum on student learning.
• Method : Collect quantitative data from student test scores and qualitative data from teacher interviews to provide a comprehensive evaluation.
• Design : Qualitative, ethnography.
• Goal : To study cultural practices in rural communities.
• Method : The researcher spends an extended period within the community, observing daily activities and conducting informal interviews.

Tips for Choosing the Right Research Design

• Align with Research Question : Choose a design that directly addresses the research question and allows for valid answers.
• Consider Data Type : Decide whether the research requires quantitative (numerical) or qualitative (textual or observational) data.
• Assess Feasibility : Take into account time, resources, and access to participants when selecting a design.
• Ensure Ethical Compliance : Make sure the design is ethically sound, with informed consent and confidentiality for participants.
• Anticipate Limitations : Be aware of potential limitations in each design type and how they might affect your findings.

Challenges in Research Design

• Sample Selection Bias : Choosing a non-representative sample can lead to biased results and impact the study’s validity.
• Data Collection Constraints : Limitations in resources or participant access may affect data quality.
• Ethical Concerns : Research involving vulnerable populations or sensitive topics requires careful ethical consideration.
• External Validity : Some designs, like case studies, may have limited generalizability beyond the studied context.

Research design is a critical component of the research process, as it determines how a study is structured, conducted, and analyzed. By choosing the appropriate design—whether qualitative, quantitative, or mixed methods—researchers ensure that they answer their questions effectively, producing credible, reliable, and valid results. A solid research design aligns with the study’s objectives, considers resources and ethical issues, and anticipates limitations to provide meaningful contributions to knowledge.

• Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . SAGE Publications.
• Trochim, W. M., & Donnelly, J. P. (2008). The Research Methods Knowledge Base . Cengage Learning.
• Saunders, M., Lewis, P., & Thornhill, A. (2019). Research Methods for Business Students . Pearson Education.
• Yin, R. K. (2017). Case Study Research and Applications: Design and Methods . SAGE Publications.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
• Text Mining and Computational Text Analysis
• Evidence Synthesis/Systematic Reviews
• Get Data, Get Help!

About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Oct 25, 2024 11:24 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

Research Methodology: Overview of Research Methodology

• Overview of Research Methodology
• General Encyclopedias on Research Methodology
• General Handbooks on Research Methodology
• Focus Groups
• Case Studies
• Cost Benefit Analysis
• Participatory Action Research
• Archival Research
• Data Analysis

Research Methods Overview

If you are planning to do research - whether you are doing a student research project,  IQP,  MQP, GPS project, thesis, or dissertation, you need to use valid approaches and tools to set up your study, gather your data, and make sense of your findings. This research methods guide will help you choose a methodology and launch into your research project. 

Data collection and data analysis are  research methods  that can be applied to many disciplines. There is Qualitative research and Quantitative Research. The focus of this guide, includes most popular methods including: 

focus groups

case studies

We are happy to answer questions about research methods and assist with choosing a method that is right for your research in person or online. below is a video on how to book a research consultation

"How-To": Booking a Research Consultation

" Research Data Management " by  Peter Neish  is marked with  CC0 1.0 .

Research Design vs Research Method

What is the difference between Research Design and Research Method?

Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Which research method should I choose ?

It depends on your research goal.  It depends on what subjects (and who) you want to study.  Let's say you are interested in studying what makes people happy, or why some students are more conscious about recycling on campus.  To answer these questions, you need to make a decision about how to collect your data.  Most frequently used methods include:

• Observation / Participant Observation
• Experiments
• Secondary Data Analysis / Archival Study
• Mixed Methods (combination of some of the above)

One particular method could be better suited to your research goal than others, because the data you collect from different methods will be different in quality and quantity.   For instance, surveys are usually designed to produce relatively short answers, rather than the extensive responses expected in qualitative interviews.

What other factors should I consider when choosing one method over another?

Time for data collection and analysis is something you want to consider.  An observation or interview method, so-called qualitative approach, helps you collect richer information, but it takes time.  Using a survey helps you collect more data quickly, yet it may lack details.  So, you will need to consider the time you have for research and the balance between strengths and weaknesses associated with each method (e.g., qualitative vs. quantitative).

Research Data Management

Research Data Management (RDM) refers to how you are going to keep and share your data over longer time frame - like after you graduate. It is defined as the organization, documentation, storage, and  preservation  of the  data  resulting from the research process, where data can be broadly defined as the outcome of experiments or observations that validate research findings, and can take a variety of forms including numerical output ( quantitative data ),  qualitative data , documentation, images, audio, and video.

"Research Design"  by  George C Gordon Library  is licensed under  CC BY 4.0  / A derivative from the  original work

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• Last Updated: Sep 12, 2024 6:11 PM
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How to identify your research methods

A short guide to research design and some common research methods

How to use this guide

If you are planning a research project, or just curious to learn more about research, you can use this guide to get an overview of some key terms.

However, research methods vary hugely across different subject areas. Your course materials and tutors will be the best guide to doing research in your subject.

If you are doing a dissertation or large research project, we have guidance to help you with each stage of the process:

How to plan a dissertation or final year project

Research questions

Before you choose your research methods, you need to identify one or more research questions , which you may be able to break down into more specific research objectives . In other words, what are you trying to find out?

Some examples of approaches to research include:

Scholarship of discovery

• Explore an under-researched area
• Develop or test out a new methodology or technique
• Extend or develop a previous study

Scholarship of summary

• Review the existing knowledge in a specific field
• Make connections between disciplines

Scholarship of application

• Replicate an existing study/approach in a different setting
• Apply a theoretical idea to a real world problem

Whichever approach you take, you need to express the purpose of your research in one or more clear research questions. The aim of your project will be to answer those questions. Guidance on Writing Strong Research Questions (external website)

Research design

It’s important to spend time planning your research. You need to choose the methods that will allow you to answer your research questions.

Key issues to consider will include:

• Are you aiming to prove/disprove a hypothesis, or explore a more open question?
• What constitutes sufficient data for your research (whether experimental data or other forms of data such as primary sources)?
• How will you ensure that your data is valid ? I.e. how confidently will you be able to report on the findings of your research?
• Is your data reliable ? Have you been objective and would other researchers be able to replicate your project with the same results?
• Is your research plan feasible with the time and resources that you have available?

One of the best ways to develop your own research methodology is to learn about the approaches used by other researchers in your subject area.

What can you learn from their research design (including the limitations and shortcomings that they may have identified)?

Find out about research methods in your subject area. Review course materials or talk to your tutors.

Use library resources to find existing research in your subject area

Primary and secondary sources

Your research is likely to involve the use of either primary sources, secondary sources or both.

• Primary sources are the raw data of your research and can include pretty much anything that has not already been analysed. Primary sources include your own experimental data, data taken from other shared datasets and any other materials such as text, film, music or images that you are analysing as part of your research. 
• Secondary sources include material that has already been published that you are using as part of your literature review or to help inform your thinking about a topic more broadly. Secondary sources include an element of interpretation or analysis by their authors and include reference books, journal articles or blog posts. 

Imperfect research

All research is imperfect. It is your job as a researcher to do your best to mitigate potential issues with your research, but also to recognise that your findings may include a number of limitations. 

Some research may produce unexpected or negative results. Although that may feel frustrating or disappointing, it does not make your findings any less interesting! Identifying and explaining mistakes and issues is part and parcel of the research process, so be honest and save other researchers from repeating those mistakes in their future research.

Types of research

Here is an overview of some commonly-used research definitions and methods.

Experimental research

Experimental research usually follows the principles of the scientific method. The researcher:

• Makes an observation to describe a problem.
• Formulates a testable hypothesis (prediction).
• Uses experiments to test the hypothesis.
• Adapts the hypothesis in light of the findings.

Experimental research usually involves a variable that can be controlled by the researcher and a variable that can be compared. It is often (but not always) carried out in a controlled environment to ensure that the findings are as valid as possible. 

Experimental research can be time and equipment intensive, so be sure to check that you will be able to access the appropriate apparatus, tools and laboratory space at the time when you will need it.

Sometimes, but not always, experimental research can be used to make absolute claims, i.e. to prove or disprove a hypothesis. More often, it will allow the researcher to refine and adapt a hypothesis and to identify further ways to test the hypothesis experimentally.

More guidance on experimental research

Quantitative research

Quantitative research deals with quantities; i.e. numerical data. Quantitative research usually involves applying statistical techniques to identify patterns and relationships in the data. 

You might collect your own data or analyse existing data. Your tutors or your department liaison librarian can help you find suitable data sources for your subject area.

Find library help and resources for your subject

When deciding what type of data to use or create, you will need to consider:

• The size and reliability of your sample
• The quality of the data 
• What statistical analysis technique will you use? What data will you need to be able to perform the analysis that you are aiming for?
• Any restrictions on using the data, for example in relation to research ethics or data protection

View resources on statistical analysis

Qualitative research

Qualitative research aims to explore the nuances of a problem, or to investigate an area in depth. It tends to focus on words and language as a way to explore the varied perspectives that may be involved in the area of research. It may also make use of visual data.

Qualitative research may draw on a very small sample to explore individual experiences in great depth (for example through one or more interviews), or it may use a large sample to investigate a range of opinions (for example through a survey).

Sometimes qualitative data will be used on its own, for example to develop one or more case studies. However, often qualitative data can also be analysed or 'coded' to identify themes, use of language, or to produce numerical data. These forms of analysis can then be used to make generalisations or draw conclusions. 

It should be noted, however, that conclusions based on qualitative data should be cautious and limitations and potential sources of bias should always be identified and acknowledged.  

There are lots of ways to collect qualitative data, each with their own advantages and disadvantages. For example:

Mixed-Methods research

Mixed methods research combines qualitative and quantitative approaches within a single study.

You might want to use mixed methods research if:

• You need both qualitative and quantitative data to answer your research questions.
• You want to combine the strengths (and mitigate the limitations) of qualitative and quantitative approaches.

Some challenges in mixed methods research are:

• You need skills in both qualitative and quantitative methods. You might find it easier to start with a project that uses just one method.
• You will need to allow time to collect and analyse two different types of data.
• You will need to think about how to combine the analysis of the two different types of data.

Creswell, J.W. and Plano Clark, V.L. (2011) Designing and conducting mixed methods research . Second edition. Sage: Thousand Oaks, CA.

Using critical theory

Critical theory is an approach to research that goes beyond the traditional formulations of quantitative and qualitative research to explore and challenge the socio-historical constructs of knowledge production. 

Critical theory is not only about describing the way things are, but is about understanding why things are the way they are. It draws on an analysis of historical processes combined with observation and interpretation of primary sources and data to explore the structural relations, inequalities and repressions that have contributed to the establishment of the status quo. 

Your role as a critical researcher is to understand the discourses and paradigms that have shaped your particular area of study and how it intersects with other related areas. You will also need to unpack your own ideological baggage to understand how your experience may inform your approach to your research area. What are the assumptions or implicit biases that underlie your own belief systems?

Critical theory recognises that no research is ever truly objective. The best you can do as a researcher is to identify the theoretical, social and cultural underpinnings of your work and to acknowledge that your conclusions should be understood within that wider context.

Archival research

Archival research involves studying materials held in physical or digital collections. 

Some archives can be accessed online. In other cases you will need to visit in person and order documents in advance to allow staff to access them and make them available to you. Each archive will have its own regulations and procedures - make sure you read and understand them before you visit. 

Working in archives can be an extremely rewarding and exciting experience that gives you first-hand access to documents or materials that may be extremely rare or little-viewed.

How to find archival sources

• Research methods (statistical research)
• How to plan a dissertation project
• How to gain ethical approval

Further resources

• Search the Library Subject Guides to access guidance and resources targeted to your subject area.
• Sage research methods is an online resource of SAGE content for research methods students and researchers, including SAGE book, journal, and reference content, research methods cases, methods videos and methods datasets.

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Research Methods | Definition, Types, Examples

Research methods are specific procedures for collecting and analysing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs quantitative : Will your data take the form of words or numbers?
• Primary vs secondary : Will you collect original data yourself, or will you use data that have already been collected by someone else?
• Descriptive vs experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyse the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analysing data, examples of data analysis methods, frequently asked questions about methodology.

Data are the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.

Primary vs secondary data

Primary data are any original information that you collect for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary data are information that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data. But if you want to synthesise existing knowledge, analyse historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare them for analysis.

Data can often be analysed both quantitatively and qualitatively. For example, survey responses could be analysed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that were collected:

• From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions.

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that were collected either:

• During an experiment.
• Using probability sampling methods .

Because the data are collected and analysed in a statistically valid way, the results of quantitative analysis can be easily standardised and shared among researchers.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

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.

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.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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