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Social Research Methods
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Social Research Methods
Qualitative and Quantitative Approaches

Third Edition
December 2025 | 672 pages | SAGE Publications, Inc
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Social Research Methods: Qualitative and Quantitative Approaches equips students with the tools they need to conduct meaningful research across the social sciences. By blending qualitative and quantitative methods, it helps graduate students not only understand how to use research techniques—but also when and why to use them. Drawing on real-world examples from psychology, sociology, anthropology, health, and education, the book brings abstract concepts to life and shows students how to apply them in their own work. The Third Edition streamlines content while also expanding coverage of key topics like sampling, interviewing, and data analysis, making it easier for instructors to teach core methods and for students to build lasting research skills.
 
Preface
 
Acknowledgments
 
About the Authors
 
Chapter 1: The Foundations of Social Research
Introduction

 
What Is Social Science Research?

 
Ethics and Social Science

 
The Language and Logic of Social Research

 
Variables: The Joy of Measurement

 
Concepts and Measurement

 
Conceptual and Operational Definitions

 
Levels of Measurement

 
Validity, Reliability, Accuracy, and Precision

 
Is My Measure Any Good? Determining Validity

 
The Problem with Validity

 
The Bottom Line

 
Key Concepts In This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 2: Preparing For Research
Setting Things Up

 
Ethics of Social Research

 
Theory—Explanation and Prediction

 
A Guide to Finding Research Questions, Anyway

 
Generating Types of Studies

 
The Literature Search

 
Meta-Analysis

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 3: Research Design
Introduction: What Is Research Design?

 
About Numbers and Words: The Qualitative/Quantitative Split

 
Cause and Effect

 
Units of Analysis

 
Three Decisions in Research Design

 
The Eight Types of Research Design

 
Mixed-methods Research Designs

 
Participatory and Action Research

 
The Components of a Research Design

 
The Art of Proposal Writing

 
How to Develop Your Proposal with Mentors and Peers

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 4: Experiments In Social Science
The Logic Of The Experimental Method

 
Internal and External Validity

 
Controlling for Threats to Validity

 
Factorial Designs: Main Effects and Interaction Effects

 
Field Experiments

 
Are Field Experiments Ethical?

 
Thought Experiments

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 5: Scales And Scaling
Introduction

 
Single-question Scales

 
Single-indicator Graphic Representational Scales

 
Composite (or Complex) Scales: Multiple Indicators

 
Indexes

 
Guttman Scales

 
Likert Scales

 
Item Analysis

 
Testing for Unidimensionality with Factor Analysis

 
The Semantic Differential

 
And Finally . . .

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 6: Probability Sampling
What Are Samples and Why Do We Need Them?

 
Why Samples Can Be More Accurate than Counts

 
Sampling Frames

 
Stratified Sampling

 
Cluster Sampling

 
Probability Proportionate to Size

 
How Big Should a Sample Be?

 
Probability Distributions

 
The Normal Curve and the Standard Deviation

 
The Central Limit Theorem

 
The Standard Error and Confidence Intervals

 
Small Samples: The t-Distribution

 
Estimating Proportions

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 7: Nonprobability Sampling
Introduction

 
Reasons to Use a Non-Probability Sample

 
Four Common and Two Uncommon Types of Non-Probability Samples

 
Minimum Sizes for Different Types of Nonprobability Samples

 
Deciding on a nonprobability sampling method and sample size

 
And Finally . . .

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 8: Interviewing and Focus Groups
The Big Picture

 
Interview Control

 
Unstructured Interviewing

 
Probing

 
Learning to Interview

 
Positionality and Presentation of Self

 
Using a Voice Recorder

 
Using Visual Cues, Like Photos in Interviews

 
Focus Groups

 
Response Effects

 
Respondent/Informant Accuracy

 
Key concepts in this Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 9: Survey Research
Introduction

 
Methods for Collecting Questionnaire Data

 
When to Use what

 
Working with Interviewers

 
Closed- Versus Open-ended Questions

 
Fourteen Rules for Question Wording and Format

 
Pretesting and Learning from Mistakes

 
Translation and Back Translation

 
The Response Rate Problem

 
Improving the Response Rate: Dillman’s Total Design Method

 
Cross-sectional and Longitudinal Studies

 
Some Specialized Survey Methods

 
Key concepts in this Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 10: Collecting Social Network Data
Social Networks

 
Two Kinds of Social Networks

 
Doing Network Analysis

 
Collecting Whole (Sociocentric) Network Data

 
Collecting Personal (Egocentric) Network Data

 
Key concepts in this Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 11: Fieldwork: Direct and Participant Observation
Introduction

 
Some History: Observing Behavior in the Lab

 
Direct Observation in the Wild

 
Reactive Observation: Continuous Monitoring and Spot Sampling

 
Spot Sampling

 
A Few Final Words on Reactive Observation

 
Unobtrusive Observation

 
Disguised Field Observation

 
Indirect Observation

 
Participant Observation

 
Different Roles in Participant Observation

 
Doing Participant Observation

 
The Skills of a Participant Observer

 
Hanging Out, Gaining Rapport

 
Objectivity

 
Insider Research: Studying Your Own Culture

 
Gender, Parenting, and Other Personal Characteristics

 
Sex and Fieldwork

 
Surviving Fieldwork

 
Leaving the Field

 
Key concepts in this Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 12: Analyzing Text: Grounded Theory and Content Analysis
Introduction

 
Overview of Grounded Theory

 
Content Analysis

 
Doing Classical Content Analysis

 
Intercoder Reliability

 
Automated Content Analysis: Content Dictionaries

 
AI and Text Analysis

 
Key Concepts in this Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 13: Discourse Analysis
Introduction

 
Conversation Analysis

 
Taking Turns in a Jury

 
Narrative Analysis

 
Phenomenological Analysis of Narratives

 
Language in Use

 
Critical Discourse Analysis: Language and Power

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 14: Univariate and Bivariate Analysis
Introduction

 
Univariate Analysis: Raw Data

 
Frequency Distributions

 
Measures of Central Tendency

 
Outliers and Skewness

 
Visualizing Data

 
Measures of Dispersion: Variance and the Standard Deviation

 
The Logic of Hypothesis Testing

 
Testing the Means of Large Samples: Using z-Scores

 
The Univariate Chi-square Test

 
Testing Relations: Bivariate Analysis

 
The t test: Comparing Two Means

 
ANOVA—Analysis of Variance

 
Visualizing the Direction and Shape of Covariations

 
Crosstabs of Nominal Variables

 
Correlation and Cause: Antecedent and Intervening Variables

 
Chi-Square for Bivariate Comparisons

 
Testing the Association between Ordinal Variables

 
What to Use for Nominal and Ordinal Variables

 
Correlation: The Powerhouse Statistic for Covariation

 
Regression

 
Advantages and disadvantages of r and r^2

 
Nonlinear Relations

 
Statistical Significance, the Shotgun Approach, and Other Issues

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 15: Multivariate Analysis
Introduction

 
Elaboration: Controlling for Independent Variables

 
Car Wrecks and Teenage Births

 
The Multiple Regression Equation

 
Using Multiple Regression to Solve the MVD-TEENBIRTH Puzzle

 
Path Analysis

 
Factor Analysis

 
Discriminant Function Analysis (DFA)

 
And Finally . . .

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 16: Analyzing Network Data
Introduction: About Matrices

 
Analyzing Relational Data: MDS and Cluster Analysis

 
Analyzing Social Network Data

 
Analyzing Whole (Sociocentric) Network Data

 
Analyzing Personal (Egocentric) Network Data

 
“It’s Not what You Know, It’s Who You Know”

 
Adding Network Data to the Classic Recipe

 
Affiliation Matrices

 
Semantic Networks

 
Key Concepts in This Chapter

 
Summary

 
Exercises

 
Further Reading

 
 
Chapter 17: On Writing Up
Introduction

 
Getting Your Article Published

 
 
Bibliography

The main strength of this text is coverage of both quantitative and qualitative methodology from a broad range of fields. The examples are often my students' favorite thing to discuss in class.

Erica B. Gibson
University of South Carolina

This text does an excellent job of not only showing how to practice research but also provides a detailed discussion of broader historical and philosophical contexts that are important for understanding research.

Julian Kilker
University of Nevada, Las Vegas

The depth of detailed descriptions (foundations of social research; interviewing, participant observation, field notes, and data analysis) go beyond other texts…the organization is superb.

Benedict J. Colombi
University of Arizona
Key features
NEW TO THIS EDITION:
  • New author Amber Wutich joins H. Russell Bernard for this Third Edition, and in "Amber's Corner" and "Russ's Corner" boxes they each report on their personal research experiences.
  • A reorganized chapter structure streamlines the book from 22 chapters to 17, while expanding coverage of key topics like sampling, interviewing, and data analysis.
  • Tips & Tricks and Deep Dives boxes aid in the understanding of research methods.
  • An updated and expanded section on searching the literature has been added to the discussion of setting up a research project.
  • In the discussion on research design, the authors have added detailed instruction on writing proposals for external funding.
  • In their discussion on data analysis, the authors have added new coverage on artificial intelligence and text analysis.
  • A new final chapter focuses on writing results for publication.
KEY FEATURES:
  • Unified Approach to Methods. This text breaks down the traditional divide between qualitative and quantitative research, showing students that all methods are tools available to every social scientist—regardless of discipline or philosophical stance.
  • Designed for Real Teaching Challenges. With clear chapter objectives, boxed highlights, numbered steps, and end-of-chapter summaries and exercises, the book is structured to support instructors in delivering complex material in digestible, teachable segments.
  • Ethics Embedded Throughout. Rather than isolating ethics in a single chapter, the book weaves ethical considerations into every stage of the research process—modeling for students how to think critically and responsibly as researchers.
  • Flexible for Course Design. The modular structure allows instructors to tailor the book to their course needs—pairing sampling with data analysis or interviewing with qualitative analysis—while still maintaining a coherent learning arc.
  • Grounded in Field Experience. Written by seasoned researchers and teachers, the book reflects decades of hands-on experience and pedagogical insight, helping students not just learn methods, but also understand how and why they work in real-world research.

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