Sidebars

By chapter and section number:

1. Introduction

1.0. The Language of Science

1.1. Deeper Dive: Ontology and Epistemology

2. Using Sociology in Everyday Life

2.1. Researchers and Research Communities

2.3. Finding Sociological Jobs

2.5. Sociology for the People: A Q&A with Sarah Dewees

3. The Role of Theory in Research

3.2. Sociology across Boundaries: A Q&A with Chinyere Osuji

3.3. Deeper Dive: Revising Our Social Realities

3.3. Deeper Dive: Idiographic and Nomothetic Explanations

4. Research Questions

4.1. Asking Questions in Need of Answers: A Q&A with Joyce Rothschild

5. Research Design

5.2. Peer Review: What Makes a Science a Science

5.3. Search Operators

5.4. A Hierarchy of Evidence?

5.4. How to Read Social Science Writing Strategically

5.6. Mapping the Social World: A Q&A with Jennifer A. Johnson

6. Sampling

6.1. Deeper Dive: Ecological Fallacies

6.2. Deeper Dive: Sampling Gone Wrong

6.4. Deeper Dive: Sampling Gone Wrong (Again)

7. Measuring the Social World

7.1. The Bell Curve and Its Critics, by Andrew Park

7.2. Deeper Dive: Interval and Ratio Levels of Measurement

7.4. Social Desirability in Political Polling: The Wilder Effect and Shy Trump Voters

8. Ethics

8.1. The Nuremberg Code

8.2. The Journalist and the Ethnographer, by Victor Tan Chen

8.3. Professional Codes of Ethics

8.4. Studying Vulnerable Populations and Polarized Issues: A Q&A with Didem Danış

9. Ethnography

9.2. Ethnography as Empathetic Understanding: A Q&A with Amy L. Best

10. In-Depth Interviews

10.4. Capturing Stories that Resonate: A Q&A with Allison Pugh

11. Qualitative Data Analysis

11.0. Transcribing Interview Data

11.1. Deeper Dive: Axial and Selective Coding

11.1. Actionable Research: A Q&A with Leslie Martin

12. Experiments

12.3. Deeper Dive: Problems with Pretests

12.5. Deeper Dive: Time-Series Design

13. Surveys

13.1. Response Rates and the Dirty Secret of Political Polling

14. Quantitative Data Analysis

14.0. Statistical Analysis Programs

14.1. Deeper Dive: Entering Your Own Data in SPSS

14.1. Searching a Data Repository

14.2. Deeper Dive: Treating Ordinal-Level Variables as Scale-Level Variables

14.2. Deeper Dive: Measures of Variability

14.2. Quantifying and Comparing Life Outcomes: A Q&A with Elyas Bakhtiari

14.3. General Tips for Reading Data Tables

14.3. Understanding Null Hypothesis Testing

14.3. Interpreting Inferential Statistics

A. Presenting, Writing, and Publishing

A.2. Sociology Professional Conferences

A.2. Deeper Dive: Tips for Presentation Slides

A.3. Deeper Dive: Using Zotero to Manage Your References

A.4. Writing Op-eds, by Victor Tan Chen

Figures

By numbering within chapter:

3.1. Macro, Meso, and Micro Levels of Analysis

3.2. The Theoretical and Empirical Levels of Research

3.3. The Relationships between Concepts

4.1. Example of a Concept Map

4.2. The Wheel of Science

4.3. Deduction: From Abstract to Concrete

4.4. Induction: From Concrete to Abstract

5.1. Google Scholar

5.2. Literature Review Matrix

5.3. Organizing Your Literature Review as a Funnel

6.1. Units of Analysis, Populations and Samples

6.2. Target Populations and Sampling Frames

6.3. Respondents versus Nonrespondents

6.4. Systematic Sampling

6.5. An Example of Periodicity When Using Systematic Sampling

6.6. Examples of Proportionate and Disproportionate Stratified Sampling: Racial and Ethnic Groups in Richmond, Virginia

6.7. An Example of Cluster Sampling: Surveying Public Librarians in Virginia

6.8. Snowball Sampling

6.9. Example of Quota Sampling

7.1. The Conceptualization-Operationalization-Measurement (COM) Process

7.2. Nominal Level of Measurement Example: Dog Breeds

7.3. Ordinal Level of Measurement Example: Perceived Health

7.4. The Hierarchy of Levels of Measurement

7.5. Fahrenheit, Celsius, and Kelvin Temperature Scales

7.6. Social Progress Index

7.7. Comparing Reliability and Validity

9.1. The Participation Continuum

9.2. Organizational Permission Letter

9.3. The Disclosure Continuum

9.4a. Field Jottings

9.4b. Vignette

9.5a. Organizing Field Notes by Event or Organization

9.5b. Organizing Field Notes by Date

9.6. Example of a Field Note

10.1. Interview Guide with General Topics

10.2. Interview Guide with Topics and Questions

10.3. Supplemental Questionnaire

10.4. Asking Sensitive Questions

10.5. Recruitment Flyer

11.1. Automated Transcription Using NVivo

11.2. Coding Using NVivo

11.3. Compiling Coding References

11.4. Interviewee Spreadsheet

11.5. Folder of Coding Memos

11.6. Coding Memo

11.7. Published Manuscript Incorporating Coding

11.8. Nesting Codes

11.9. Two-by-Two Table

11.10. Complex Typologies

11.11. Concept Maps

11.12. Blockquotes in Qualitative Studies

11.13. Introducing Interviewees

11.14. Editing Interview Quotes for Clarity

11.15. Extended Descriptions of Interviewees

12.1. One-Group Posttest-Only Design

12.2. One-Group Pre-Post Design

12.3. Two-Group Pretest–Posttest Design

12.4. A Classic Experiment: Two-Group Randomized Pre-Post Design

12.5. Two-Group Randomized Pre-Post Design with Scores (Math App Example)

12.6. Two-Group Randomized Posttest-Only Design

12.7. Outcomes at 24 Years or Older for Children Who Moved Before They Were 13: An Analysis of Moving to Opportunity Data by Chetty et al. (2016)

12.8. Appointments Obtained for Mental Health Therapy by the Class, Race, and Gender of the Help-Seeker: An Audit Study by Kugelmass (2016)

12.9. The Effect of a Criminal Record on Black and White Job Applicants: An Audit Study by Pager (2003)

12.10. Nonequivalent Control Group Design

12.11. Educational Attainment of Cambodian Students by Dropout Risk Score: Regression Discontinuity Analysis by Filmer and Schady (2009)

12.12. The Logic of the Differences-in-Differences Method in a Minimum-Wage Study by Card and Krueger (1994)

12.13. One-Group Time-Series Design

12.14. Time-Series Outcome When the Treatment Has an Effect

12.15. Oklahoma County General Fertility Rate over Time: A Time-Series Experimental Design (Rodgers et al. 2005)

12.16. Multiple Time-Series Design with Two Comparison Groups

13.1. 1890 Census Form

13.2. Letter with a Survey Link

13.3. Questions for Interviewers

13.4. Question Order Effects

13.5. Mutually Exclusive Response Options

13.6. Collectively Exhaustive Response Options

13.7. Double-Barreled Response Options

13.8. Survey Questions in a Matrix Format

13.9. Filter Questions

14.1. Codebook Excerpt from the LIFE Dataset of the Mexican Migration Project

14.2. Levels of Measurement

14.3. Numerical Codes for a Nominal-Level Variable’s Response Options

14.4. Numerical Codes for an Ordinal-Level Variable’s Response Options

14.5. Viewing a Dataset in SPSS

14.6. Variables in the GSS Data Explorer

14.7. Variables in the GSS Codebook

14.8. Showing Value Labels for Variables in SPSS

14.9. Listing the Value Labels for a Variable

14.10. Breaking Down a Frequency Table

14.11. Pie Chart for Frequency of Prayer

14.12. Bar Chart for Frequency of Prayer

14.13. Frequency Distribution for a Recoded Age Variable

14.14. Histogram of the Scale-Level Age Variable

14.15. Line Graph of the Scale-Level Age Variable

14.16. Three Frequency Distributions with Their Modes Highlighted

14.17. Modes for Age and Educational Attainment

14.18. Median for Frequency of Prayer

14.19. Histograms Showing Shapes of Frequency Distributions

14.20. Mean for Frequency of Prayer, an Ordinal-Level Variable

14.21. Frequency Table from Lee et al. (2011)

14.22. Crosstabulation of Frequency of Prayer (DV) by Gender (IV) with Counts

14.23. Crosstabulation of Frequency of Prayer by Gender with Column Percentages

14.24. Crosstabulation of Frequency of Prayer by Gender with Row Percentages

14.25. Possible Relationships between Variables in a Crosstab

14.26. Possible Directions of Relationships in a Crosstabulation

14.27. Chi-Square Test for the Crosstabulation of Frequency of Prayer by Gender

14.28. Chi-Square Test for the Crosstabulation of Frequency of Prayer by Educational Attainment

14.29. Table in Kimunai et al. (2016) Presenting Crosstabulations of Healthcare Behaviors by Level of Literacy

15.1. Expert Quotes about Police Shootings in the New York Times and USA Today: A Content Analysis by Crichlow and Fulcher (2017)

15.2. Coding Instructions from Neuendorf et al. (2010)

15.3. Calculating Inter-coder Reliability in Neuendorf et al. (2010)

15.4. Frequencies of Codes in Student Comments: A Content Analysis by Chambers and Chiang (2012)

15.5. Views about Marriage Norms in U.S. Women’s Magazines from 1900 to 1979: A Quantitative Content Analysis by Cancian and Gordon (1988)

15.6. The Relationship between Gender and Scouting Activity Type: A Content Analysis by Denny (2011)

15.7. The Relationship between the Gender Category and Color Palette of Toys Sold on the Disney Store Website: A Content Analysis by Auster and Mansbach (2012)

15.8. Challenges in Coding: Pages from Anne Lister’s Diaries

A.1. Inserting Formal Hypotheses into Your Paper

Tables

By numbering within chapter:

3.1. Major Sociological Theories and the Study of Sports

3.2. Social Scientific Paradigms

4.1. Predicting the Effects of Arrest on Future Spouse Battery: Testing Theories through Deduction (Sherman and Berk 1984)

4.2. Predicting the Effects of Arrest on Future Spouse Battery: A New Theory Generated from Induction

4.3. Words to Watch for in Research Questions

6.1. When to Use Probability Sampling Strategies

6.2. When to Use Nonprobability Sampling Strategies

7.1. Sociological Examples of a Nominal Level of Measurement

7.2. Sociological Examples of an Ordinal Level of Measurement

7.3. Sociological Examples of a Scale Level of Measurement

7.4. Acceptance of Social Groups Scale

7.5. Confidence in the U.S. Federal Government: Summed Scores for Respondents’ Perceptions of the Three Branches of Government

7.6. Confidence in the U.S. Federal Government: Mean Scores for Respondents’ Perceptions of the Three Branches of Government

9.1. Examples of Ethnographies

9.2. Telling versus Showing

11.1. Typology of Parenting Approaches in Lareau (2011)

12.1. Threats to Internal Validity and Ways to Address Them

14.1. Measures of Central Tendency for Variables at the Scale, Ordinal, and Nominal Level

14.2. Measures of Variability for Variables at the Scale, Ordinal, and Nominal Level

14.3. Range, IQR, and Standard Deviation for Selected GSS Variables

14.4. Frequency Distribution and Index of Qualitative Variation for Gender and Race

14.5. Crosstabulations of Frequency of Prayer by “Comfort Theory” Independent Variables

14.6. Crosstabulations of Religious Service Attendance by “Comfort Theory” Independent Variables

14.7. The Statistical Significance of a Bivariate Relationship as Predicted by Relationship Strength and Sample Size

15.1. Examples of Content Analysis

15.2. Sample Code Sheet for Study of Kitchen Utensil Popularity over Time

A.1. In-Text Citations

A.2. References in the Works Cited Section

Videos

By numbering within chapter:

3.1. Macro and Micro Perspectives

6.1. How a Flawed Sample Sank a Major Presidential Poll

6.2. Random Sampling

6.3. Probability Sampling Strategies

6.4. Opt-In Surveys

8.1. An Inauspicious Start to an Experiment

9.1. Sidewalk, the Documentary

9.2. Street Corner Society, in Retrospect

11.1. A Typology of Parenting Approaches

12.1. Experimenter Expectancy Effects

13.1. The Up Documentary Series

13.2. Writing Survey Questions

14.5. Measures of Central Tendency

15.1. What Kitchen Utensils Say about Society