Fundamental Statistics for the Social and Behavioral Sciences

Second Edition

Howard T. Tokunaga

Other Titles in:
Psychology (General) | Quantitative Methods | Quantitative/Statistical Research (General)

January 2019 | 712 pages | SAGE Publications, Inc

Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated.

The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge.

Also new to the Second Edition -- animated video tutorials! Watch the demo video from Chapter 2 now!

Corrections: there are a small number of corrections for the text's Appendix posted here.

About the Author

Preface to the Second Edition

Preface to the First Edition

Acknowledgments

Companion Site

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

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 Formulas Introduced in This Chapter

2.11 Using IBM SPSS Software

2.12 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

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

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

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 Formulas Introduced in This Chapter

6.9 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

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

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

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

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

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

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

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

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

Tables

Appendix: Review of Basic Mathematics

Glossary

References

Index

Supplements

Instructor edge site

SAGE edge for Instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students.

Test banks in Word format and ExamView provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert your own personalized questions to effectively assess students’ progress and understanding.
Sample course syllabi for semester and quarter courses provide suggested models for structuring your courses.
Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for your course.
Multimedia content includes original SAGE videos featuring tutorials with author Howard T. Tokunaga that bring concepts to life and appeal to diverse learners.
Lecture notes summarize key concepts by chapter to help you prepare for lectures and class discussions.
Course cartridge for easy LMS integration
Answers to even-numbered questions from the text help facilitate grading.
SPSS datasets are available for use with exercises from the text.

Student edge site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

Mobile-friendly eFlashcards strengthen understanding of key terms and concepts.
Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material.
Multimedia content includes original SAGE animated tutorial videos bring concepts to life and appeal to diverse learners.
SPSS datasets are available for use with exercises from the text.

“I think this is some of the best explanation for these concepts that I have read.”

JoEllen Pederson

Longwood 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

“I think the author has a strong command and grasp of the material which he demonstrates by providing students with a multitude of examples and formulas that are easy to understand and broken down into digestible portions for students to absorb at their own pace. The writing style of the author is excellent…He spends a significant amount of time decomposing and deconstructing complex ideas related to the measures of central tendency for both novice and expert students of statistics in a user-friendly and approachable tone.”

Keith Feigenson

Albright College

“The writing style is nice and easy to follow.”

Timothy Victor

University of Pennsylvania

The book was written in a language that matches the students understanding in statistics starting from basic statistical concepts to advanced inferential statistics practices.

Dr Dessalegn Guyo

Psychology, Bowie State University

November 28, 2019

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