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Description
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.
Table of Contents
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
