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Fundamental Statistics for the Social and Behavioral Sciences
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Fundamental Statistics for the Social and Behavioral Sciences

Third Edition
August 2026 | 696 pages | SAGE Publications, Inc
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Fundamental Statistics for the Social and Behavioral Sciences is designed to help students truly understand statistics—not just how to calculate them, but how to think about them. Guiding students through the logic of statistical reasoning, Howard T. Tokunaga demonstrates how data are used to answer research questions, test hypotheses, and draw meaningful conclusions. With a focus on interpretation and communication, the book empowers students to connect statistical results to real-world research and confidently explain their findings. The Third Edition features simplified language but still highlights recently published research on topics relevant to students, continuing the book’s focus on clarity and relevance.
 
Preface
 
Acknowledgements
 
About The Authors
 
Chapter 1: Introduction to Statistics
1.1 What Is Statistics?

 
1.2 Why Learn Statistics?

 
1.3 Introduction to the Stages of the Research Process

 
1.4 Plan of the Book

 
1.5 Looking Ahead

 
1.6 Summary

 
1.7 Important Terms

 
1.8 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 2: Examining Data: Tables and Figures
2.1 An Example From the Research: Winning the Lottery

 
2.2 Why Examine Data?

 
2.3 Examining Data Using Tables

 
2.4 Grouped Frequency Distribution Tables

 
2.5 Examining Data Using Figures

 
2.6 Examining Data: Describing Distributions

 
2.7 Looking Ahead

 
2.8 Summary

 
2.9 Important Terms

 
2.10 Formula Introduced in This Chapter

 
2.11 Using IBM SPSS Software

 
2.12 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 3: Measures of Central Tendency
3.1 An Example From the Research: The 10% Myth

 
3.2 Understanding Central Tendency

 
3.3 The Mode

 
3.4 The Median

 
3.5 The Mean

 
3.6 Comparison of the Mode, Median, and Mean

 
3.7 Measures of Central Tendency: Drawing Conclusions

 
3.8 Looking Ahead

 
3.9 Summary

 
3.10 Important Terms

 
3.11 Formulas Introduced in This Chapter

 
3.12 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 4: Measures of Variability
4.1 An Example From the Research: How Many “Sometimes” in an “Always”?

 
4.2 Understanding Variability

 
4.3 The Range

 
4.4 The Interquartile Range

 
4.5 The Variance (s2)

 
4.6 The Standard Deviation (s)

 
4.7 Measures of Variability for Populations

 
4.8 Measures of Variability for Nominal Variables

 
4.9 Measures of Variability: Drawing Conclusions

 
4.10 Looking Ahead

 
4.11 Summary

 
4.12 Important Terms

 
4.13 Formulas Introduced in This Chapter

 
4.14 Using SPSS

 
4.15 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 5: Normal Distributions
5.1 Example: SAT Scores

 
5.2 Normal Distributions

 
5.3 The Standard Normal Distribution

 
5.4 Applying z-Scores to Normal Distributions

 
5.5 Standardizing Frequency Distributions

 
5.6 Looking Ahead

 
5.7 Summary

 
5.8 Important Terms

 
5.9 Formulas Introduced in This Chapter

 
5.10 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 6: Probability and Introduction to Hypothesis Testing
6.1 A Brief Introduction to Probability

 
6.2 Example: Making Heads or Tails of the Super Bowl

 
6.3 Introduction to Hypothesis Testing

 
6.4 Issues Related to Hypothesis Testing: An Introduction

 
6.5 Looking Ahead

 
6.6 Summary

 
6.7 Important Terms

 
6.8 Formula Introduced in This Chapter

 
6.9 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 7: Testing One Sample Mean
7.1 An Example From the Research: Do You Read Me?

 
7.2 The Sampling Distribution of the Mean

 
7.3 Inferential Statistics: Testing One Sample Mean (s Known)

 
7.4 A Second Example From the Research: Unique Invulnerability

 
7.5 Introduction to the t-Distribution

 
7.6 Inferential Statistics: Testing One Sample Mean (s Not Known)

 
7.7 Factors Affecting the Decision About the Null Hypothesis

 
7.8 Looking Ahead

 
7.9 Summary

 
7.10 Important Terms

 
7.11 Formulas Introduced in This Chapter

 
7.12 Using SPSS

 
7.13 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 8: Estimating the Mean of a Population
8.1 An Example From the Research: Salary Survey

 
8.2 Introduction to the Confidence Interval for the Mean

 
8.3 The Confidence Interval for the Mean (s Not Known)

 
8.4 The Confidence Interval for the Mean (s Known)

 
8.5 Factors Affecting the Width of the Confidence Interval for the Mean

 
8.6 Interval Estimation and Hypothesis Testing

 
8.7 Looking Ahead

 
8.8 Summary

 
8.9 Important Terms

 
8.10 Formulas Introduced in This Chapter

 
8.11 Using SPSS

 
8.12 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 9: Testing the Difference Between Two Means
9.1 An Example From the Research: You Can Just Wait

 
9.2 The Sampling Distribution of the Difference

 
9.3 Inferential Statistics: Testing the Difference Between Two Sample Means

 
9.4 Inferential Statistics: Testing the Difference Between Two Sample Means (Unequal Sample Sizes)

 
9.5 Inferential Statistics: Testing the Difference Between Paired Means

 
9.6 Looking Ahead

 
9.7 Summary

 
9.8 Important Terms

 
9.9 Formulas Introduced in This Chapter

 
9.10 Using SPSS

 
9.11 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 10: Errors in Hypothesis Testing, Statistical Power, and Effect Size
10.1 Hypothesis Testing vs. Criminal Trials

 
10.2 An Example From the Research: Truth or Consequences

 
10.3 Two Errors in Hypothesis Testing: Type I and Type II Error

 
10.4 Controlling Type I and Type II Error

 
10.5 Measures of Effect Size

 
10.6 Looking Ahead

 
10.7 Summary

 
10.8 Important Terms

 
10.9 Formulas Introduced in This Chapter

 
10.10 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 11: One-Way Analysis of Variance (ANOVA)
11.1 An Example From the Research: It’s Your Move

 
11.2 Introduction to Analysis of Variance (ANOVA)

 
11.3 Inferential Statistics: One-Way Analysis of Variance (ANOVA)

 
11.4 A Second Example: The Parking Lot Study Revisited

 
11.5 Analytical Comparisons Within the One-Way ANOVA

 
11.6 Looking Ahead

 
11.7 Summary

 
11.8 Important Terms

 
11.9 Formulas Introduced in This Chapter

 
11.10 Using SPSS

 
11.11 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 12: Two-Way Analysis of Variance (ANOVA)
12.1 An Example From the Research: Vote—or Else!

 
12.2 Introduction to Factorial Research Designs

 
12.3 The Two-Factor (A × B) Research Design

 
12.4 Introduction to Analysis of Variance (ANOVA) for the Two-Factor Research Design

 
12.5 Inferential Statistics: Two-Way Analysis of Variance (ANOVA)

 
12.6 Investigating a Significant A × B Interaction Effect: Analysis of Simple Effects

 
12.7 Looking Ahead

 
12.8 Summary

 
12.9 Important Terms

 
12.10 Formulas Introduced in This Chapter

 
12.11 Using SPSS

 
12.12 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 13: Correlation
13.1 An Example From the Research: It’s Good for You!

 
13.2 Introduction to the Concept of Correlation

 
13.3 Inferential Statistics: Pearson Correlation Coefficient

 
13.4 Correlating Two Sets of Ranks: The Spearman Rank-Order Correlation

 
13.5 Correlational Statistics vs. Correlational Research

 
13.6 Looking Ahead

 
13.7 Summary

 
13.8 Important Terms

 
13.9 Formulas Introduced in This Chapter

 
13.10 Using SPSS

 
13.11 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 14: Linear Regression and Multiple Correlation
14.1 Predicting One Variable From Another: Linear Regression

 
14.2 Correlation With Two or More Predictors: Introduction to Multiple Correlation and Regression

 
14.3 Looking Ahead

 
14.4 Summary

 
14.5 Important Terms

 
14.6 Formulas Introduced in This Chapter

 
14.7 Using SPSS

 
14.8 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Chapter 15: Chi-Square
15.1 An Example From the Research (One Categorical Variable): Are You My Type?

 
15.2 Introduction to the Chi-Square Statistic

 
15.3 Inferential Statistic: Chi-Square Goodness-of-Fit Test

 
15.4 An Example From the Research (Two Categorical Variables): Seeing Red

 
15.5 Inferential Statistic: Chi-Square Test of Independence

 
15.6 Parametric and Nonparametric Statistical Tests

 
15.7 Looking Ahead

 
15.8 Summary

 
15.9 Important Terms

 
15.10 Formulas Introduced in This Chapter

 
15.11 Using SPSS

 
15.12 Exercises

 
Answers to Learning Checks

 
Answers to Odd-Numbered Exercises

 
 
Tables
 
Appendix
 
Glossary
 
References

Fundamental Statistics for the Social and Behavioral Sciences is an excellent choice for an undergraduate-level first statistics course. It provides fairly large breadth while also providing just enough depth for students to understand the purpose of statistical methods in different types of research scenarios. It does a particularly good job of including only the most necessary computational details and avoids getting bogged down by technical jargon and equations that may turn social science students away from methodology.

Brooke Magnus
Boston College

Fundamental Statistics for the Social and Behavioral Sciences is very clearly written and well-tailored to psychology undergraduates. I greatly appreciate how many opportunities it gives students to practice what they are learning, as that is crucial to success in statistics. It does a better job than most texts in explaining confidence intervals, which is crucial to help students avoid developing misconceptions in that area. The book's integration of SPSS is also helpful for any instructor that uses that program.

Megan M. Ringel
St. Edward's University

I appreciate the structures, the simplicity in the language, the clarity and the ability to pull material that is appropriate for college level courses.

Cristine Rego
Fleming College
Key features
NEW TO THIS EDITION:
  • To make the new edition as brief and concise as possible, the author simplified the language and removed unnecessary details and discussion, reducing chapter lengths by 5-10%.
  • The book includes more end-of-chapter exercises, which have been updated using recently published research as their foundation.
  • SPSS demonstrations are updated using Version 31.
  • Chapter-specific content changes include:
    • Chapter 1 (Introduction to Statistics) uses recently published research studies throughout, featuring topics more relevant to students, such as fear of missing out (FOMO), cryptocurrency, legalization of cannabis, Gen Z, COVID, and fake news.
    • Chapter 6 (Probability and Introduction to Hypothesis Testing) features an updated Super Bowl example that introduces and illustrates the process of hypothesis testing.
    • Chapter 8's (Estimating the Mean of a Population) main research example, involving data from an actual national salary survey, has been updated throughout with more current salary data.
KEY FEATURES:
  • Every chapter is crafted with clarity and approachability, making complex statistical concepts understandable for students at all levels.
  • Emphasizes statistical reasoning and interpretation, guiding students to understand not just how to calculate statistics, but why they matter and how to communicate results.
  • Published studies and practical scenarios illustrate how statistical procedures are used to answer meaningful research questions in the social and behavioral sciences.
  • Step-by-step presentations of concepts and techniques support students in both traditional and online learning environments.
  • End-of-chapter SPSS screenshots and walkthroughs guide students in conducting analyses and interpreting output using industry-standard software.
  • Comprehensive coverage of data visualization—including bar charts, line graphs, scatterplots, and more—shows students how to present findings effectively.
  • Numerous end-of-chapter exercises provide instructors with options for homework, practice, and assessment.

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