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Statistics for the Behavioral Sciences
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Statistics for the Behavioral Sciences

Third Edition
July 2017 | 816 pages | SAGE Publications, Inc
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The engaging Third Edition of Statistics for the Behavioral Sciences shows students that statistics can be understandable, interesting, and relevant to their daily lives. Using a conversational tone, award-winning teacher and author Gregory J. Privitera speaks to the reader as researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills when working through carefully developed problems and exercises that include current research and seamless integration of SPSS. This edition will not only prepare students to be lab-ready, but also give them the confidence to use statistics to summarize data and make decisions about behavior.

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About the Author
 
Acknowledgments
 
Preface to the Instructor
 
To the Student—How to Use SPSS With This Book
 
PART I. INTRODUCTION AND DESCRIPTIVE STATISTICS
 
Chapter 1. Introduction to Statistics
1.1 The Use of Statistics in Science

 
1.2 Descriptive and Inferential

 
1.3 Research Methods and Statistics

 
1.4 Scales of Measurement

 
1.5 Types of Variables for Which Data Are Measured

 
1.6 Research in Focus: Evaluating Data and Scales of Measurement

 
1.7 SPSS in Focus: Entering and Defining Variables

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 2. Summarizing Data: Frequency Distributions in Tables and Graphs
2.1 Why Summarize Data?

 
2.2 Frequency Distributions for Grouped Data

 
2.3 Identifying Percentile Points and Percentile Ranks

 
2.4 SPSS in Focus: Frequency Distributions for Quantitative Data

 
2.5 Frequency Distributions for Ungrouped Data

 
2.6 Research in Focus: Summarizing Demographic Information

 
2.7 SPSS in Focus: Frequency Distributions for Categorical Data

 
2.8 Pictorial Frequency Distributions

 
2.9 Graphing Distributions: Continuous Data

 
2.10 Graphing Distributions: Discrete and Categorical Data

 
2.11 Research in Focus: Frequencies and Percents

 
2.12 SPSS in Focus: Histograms, Bar Charts, and Pie Charts

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 3. Summarizing Data: Central Tendency
3.1 Introduction to Central Tendency

 
3.2 Measures of Central Tendency

 
3.3 Characteristics of the Mean

 
3.4 Choosing an Appropriate Measure of Central Tendency

 
3.5 Research in Focus: Describing Central Tendency

 
3.6 SPSS in Focus: Mean, Median, and Mode

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 4. Summarizing Data: Variability
4.1 Measuring Variability

 
4.2 The Range

 
4.3 Research in Focus: Reporting the Range

 
4.4 Quartiles and Interquartiles

 
4.5 The Variance

 
4.6 Explaining Variance for Populations and Samples

 
4.7 The Computational Formula for Variance

 
4.8 The Standard Deviation

 
4.9 What Does the Standard Deviation Tell Us?

 
4.10 Characteristics of the Standard Deviation

 
4.11 SPSS in Focus: Range, Variance, and Standard Deviation

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
PART II. PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS
 
Chapter 5. Probability
5.1 Introduction to Probability

 
5.2 Calculating Probability

 
5.3 Probability and Relative Frequency

 
5.4 The Relationship Between Multiple Outcomes

 
5.5 Conditional Probabilities and Bayes’s Theorem

 
5.6 SPSS in Focus: Probability Tables

 
5.7 Probability Distributions

 
5.8 The Mean of a Probability Distribution and Expected Value

 
5.9 Research in Focus: When Are Risks Worth Taking?

 
5.10 The Variance and Standard Deviation of a Probability Distribution

 
5.11 Expected Value and the Binomial Distribution

 
5.12 A Final Thought on the Likelihood of Random Behavioral Outcomes

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 6. Probability, Normal Distributions, and z Scores
6.1 The Normal Distribution in Behavioral Science

 
6.2 Characteristics of the Normal Distribution

 
6.3 Research in Focus: The Statistical Norm

 
6.4 The Standard Normal Distribution

 
6.5 The Unit Normal Table: A Brief Introduction

 
6.6 Locating Proportions

 
6.7 Locating Scores

 
6.8 SPSS in Focus: Converting Raw Scores to Standard z Scores

 
6.9 Going From Binomial to Normal

 
6.10 The Normal Approximation to the Binomial Distribution

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 7. Probability and Sampling Distributions
7.1 Selecting Samples From Populations

 
7.2 Selecting a Sample: Who’s In and Who’s Out?

 
7.3 Sampling Distributions: The Mean

 
7.4 Sampling Distributions: The Variance

 
7.5 The Standard Error of the Mean

 
7.6 Factors That Decrease Standard Error

 
7.7 SPSS in Focus: Estimating the Standard Error of the Mean

 
7.8 APA in Focus: Reporting the Standard Error

 
7.9 Standard Normal Transformations With Sampling Distributions

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
PART III. MAKING INFERENCES ABOUT ONE OR TWO MEANS
 
Chapter 8. Hypothesis Testing: Significance, Effect Size, and Power
8.1 Inferential Statistics and Hypothesis Testing

 
8.2 Four Steps to Hypothesis Testing

 
8.3 Hypothesis Testing and Sampling Distributions

 
8.4 Making a Decision: Types of Error

 
8.5 Testing for Significance: Examples Using the z Test

 
8.6 Research in Focus: Directional Versus Nondirectional Tests

 
8.7 Measuring the Size of an Effect: Cohen’s d

 
8.8 Effect Size, Power, and Sample Size

 
8.9 Additional Factors That Increase Power

 
8.10 SPSS in Focus: A Preview for Chapters 9 to 18

 
8.11 APA in Focus: Reporting the Test Statistic and Effect Size

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 9. Testing Means: One-Sample and Two-Independent- Sample t Tests
9.1 Going From z to t

 
9.2 The Degrees of Freedom

 
9.3 Reading the t Table

 
9.4 One-Sample t Test

 
9.5 Effect Size for the One-Sample t Test

 
9.6 SPSS in Focus: One-Sample t Test

 
9.7 Two-Independent-Sample t Test

 
9.8 Effect Size for the Two-Independent- Sample t Test

 
9.9 SPSS in Focus: Two-Independent- Sample t Test

 
9.10 APA in Focus: Reporting the t Statistic and Effect Size

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 10. Testing Means: The Related-Samples t Test
10.1 Related and Independent Samples

 
10.2 Introduction to the Related-Samples t Test

 
10.3 The Related-Samples t Test: Repeated-Measures Design

 
10.4 SPSS in Focus: The Related-Samples t Test

 
10.5 The Related-Samples t Test: Matched-Pairs Design

 
10.6 Measuring Effect Size for the Related-Samples t Test

 
10.7 Advantages for Selecting Related Samples

 
10.8 APA in Focus: Reporting the t Statistic and Effect Size for Related Samples

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 11. Estimation and Confidence Intervals
11.1 Point Estimation and Interval Estimation

 
11.2 The Process of Estimation

 
11.3 Estimation for the One-Sample z Test

 
11.4 Estimation for the One-Sample t Test

 
11.5 SPSS in Focus: Confidence Intervals for the One-Sample t Test

 
11.6 Estimation for the Two-Independent-Sample t Test

 
11.7 SPSS in Focus: Confidence Intervals for the Two-Independent- Sample t Test

 
11.8 Estimation for the Related-Samples t Test

 
11.9 SPSS in Focus: Confidence Intervals for the Related-Samples t Test

 
11.10 Characteristics of Estimation: Precision and Certainty

 
11.11 APA in Focus: Reporting Confidence Intervals

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
PART IV. MAKING INFERENCES ABOUT THE VARIABILITY OF TWO OR MORE MEANS
 
Chapter 12. Analysis of Variance: One-Way Between- Subjects Design
12.1 Analyzing Variance for Two or More Groups

 
12.2 An Introduction to Analysis of Variance

 
12.3 Sources of Variation and the Test Statistic

 
12.4 Degrees of Freedom

 
12.5 The One-Way Between-Subjects ANOVA

 
12.6 What Is the Next Step?

 
12.7 Post Hoc Comparisons

 
12.8 SPSS in Focus: The One-Way Between-Subjects ANOVA

 
12.9 Measuring Effect Size

 
12.10 APA in Focus: Reporting the F Statistic, Significance, and Effect Size

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 13. Analysis of Variance: One-Way Within-Subjects (Repeated-Measures) Design
13.1 Observing the Same Participants Across Groups

 
13.2 Sources of Variation and the Test Statistic

 
13.3 Degrees of Freedom

 
13.4 The One-Way Within-Subjects ANOVA

 
13.5 Post Hoc Comparisons: Bonferroni Procedure

 
13.6 SPSS in Focus: The One-Way Within-Subjects ANOVA

 
13.7 Measuring Effect Size

 
13.8 The Within-Subjects Design: Consistency and Power

 
13.9 APA in Focus: Reporting the F Statistic, Significance, and Effect Size

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 14. Analysis of Variance: Two-Way Between-Subjects Factorial Design
14.1 Observing Two Factors at the Same Time

 
14.2 New Terminology and Notation

 
14.3 Designs for the Two-Way ANOVA

 
14.4 Describing Variability: Main Effects

 
14.5 The Two-Way Between-Subjects ANOVA

 
14.6 Analyzing Main Effects and Interactions

 
14.7 Measuring Effect Size

 
14.8 SPSS in Focus: The Two-Way Between-Subjects ANOVA

 
14.9 APA in Focus: Reporting Main Effects, Interactions, and Effect Size

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
PART V. MAKING INFERENCES ABOUT PATTERNS, FREQUENCIES, AND ORDINAL DATA
 
Chapter 15. Correlation
15.1 The Structure of a Correlational Design

 
15.2 Describing a Correlation

 
15.3 Pearson Correlation Coefficient

 
15.4 SPSS in Focus: Pearson Correlation Coefficient

 
15.5 Assumptions of Tests for Linear Correlations

 
15.6 Limitations in Interpretation: Causality, Outliers, and Restrictions of Range

 
15.7 Alternative to Pearson r: Spearman Correlation Coefficient

 
15.8 SPSS in Focus: Spearman Correlation Coefficient

 
15.9 Alternative to Pearson r: Point-Biserial Correlation Coefficient

 
15.10 SPSS in Focus: Point-Biserial Correlation Coefficient

 
15.11 Alternative to Pearson r: Phi Correlation Coefficient

 
15.12 SPSS in Focus: Phi Correlation Coefficient

 
15.13 APA in Focus: Reporting Correlations

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 16. Linear Regression and Multiple Regression
16.1 From Relationships to Predictions

 
16.2 Fundamentals of Linear Regression

 
16.3 What Makes the Regression Line the Best-Fitting Line?

 
16.4 The Slope and y-Intercept of a Straight Line

 
16.5 Using the Method of Least Squares to Find the Best Fit

 
16.6 Using Analysis of Regression to Determine Significance

 
16.7 SPSS in Focus: Analysis of Regression

 
16.8 Using the Standard Error of Estimate to Measure Accuracy

 
16.9 Introduction to Multiple Regression

 
16.10 Computing and Evaluating Significance for Multiple Regression

 
16.11 The ß Coefficient for Multiple Regression

 
16.12 Evaluating Significance for the Relative Contribution of Each Predictor Variable

 
16.13 SPSS in Focus: Multiple Regression Analysis

 
16.14 APA in Focus: Reporting Regression Analysis

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 17. Nonparametric Tests: Chi-Square Tests
17.1 Tests for Nominal Data

 
17.2 The Chi-Square Goodness-of-Fit Test

 
17.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test

 
17.4 Interpreting the Chi-Square Goodness-of-Fit Test

 
17.5 Independent Observations and Expected Frequency Size

 
17.6 The Chi-Square Test for Independence

 
17.7 The Relationship Between Chi-Square and the Phi Coefficient

 
17.8 Measures of Effect Size

 
17.9 SPSS in Focus: The Chi-Square Test for Independence

 
17.10 APA in Focus: Reporting the Chi-Square Test

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Chapter 18. Nonparametric Tests: Tests for Ordinal Data
18.1 Tests for Ordinal Data

 
18.2 The Sign Test

 
18.3 SPSS in Focus: The Related-Samples Sign Test

 
18.4 The Wilcoxon Signed-Ranks T Test

 
18.5 SPSS in Focus: The Wilcoxon Signed-Ranks T Test

 
18.6 The Mann-Whitney U Test

 
18.7 SPSS in Focus: The Mann-Whitney U Test

 
18.8 The Kruskal-Wallis H Test

 
18.9 SPSS in Focus: The Kruskal-Wallis H Test

 
18.10 The Friedman Test

 
18.11 SPSS in Focus: The Friedman Test

 
18.12 APA in Focus: Reporting Nonparametric Tests

 
Chapter Summary

 
Key Terms

 
End-of-Chapter Problems

 
 
Afterword: A Final Thought on the Role of Statistics in Research Methods
 
Appendix A. Basic Math Review and Summation Notation
A.1 Positive and Negative Numbers

 
A.2 Addition

 
A.3 Subtraction

 
A.4 Multiplication

 
A.5 Division

 
A.6 Fractions

 
A.7 Decimals and Percents

 
A.8 Exponents and Roots

 
A.9 Order of Computation

 
A.10 Equations: Solving for x

 
A.11 Summation Notation

 
Key Terms

 
Review Problems

 
 
Appendix B. SPSS General Instructions Guide
 
Appendix C. Statistical Tables
Table C.1 The Unit Normal Table

 
Table C.2 Critical Values for the t Distribution

 
Table C.3 Critical Values for the F Distribution

 
Table C.4 The Studentized Range Statistic (q)

 
Table C.5 Critical Values for the Pearson Correlation

 
Table C.6 Critical Values for the Spearman Correlation

 
Table C.7 Critical Values of Chi-Square (c2)

 
Table C.8 Distribution of Binomial Probabilities When p = .50

 
Table C.9 Wilcoxon Signed-Ranks T Critical Values

 
Table C.10A Critical Values of the Mann-Whitney U for a = .05

 
Table C.10B Critical Values of the Mann-Whitney U for a = .01

 
 
Appendix D. Chapter Solutions for Even-Numbered Problems
 
Glossary
 
References
 
Index

Supplements

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Key features

NEW TO THIS EDITION:

  • Updated scholarship includes introducing the context and research examples related to hypothesis testing in each chapter.
  • Updated learning objectives and chapter summaries improve chapter organization and help students retain important information.
  • Updated figures and tables clarify key concepts.
  • A new Appendix B connects each SPSS in Focus section to the page number where it can be found in the book and provides a general instruction guide for using SPSS.
  • All SPSS screenshots were updated for version 24 of SPSS.
  • SAGE coursepacks allows instructors to import high-quality content into their school’s learning management system (LMS) with no access codes.
  • SAGE edge provides students helpful tools, including eFlashcards, practice quizzes, a customizable action plan, and more, in one easy-to-use online environment.
  • An updated Student Study Guide also by Privitera provides even more opportunity for review, practice, and mastery of concepts.

KEY FEATURES:

  • A conversational writing style empowers students to view statistics as something they are capable of understanding and using.
  • Practice exercises place statistical analysis in the context of current scholarship.
  • All “by hand” calculations are also shown in SPSS to show how values in the formulas are computed and displayed in SPSS.
  • Making Sense sections break down the statistical concepts students typically find most challenging, review important material, and help students make sense of it.
  • SPSS in Focus sections provide step-by-step, classroom-tested instruction using practical research examples of how chapter concepts can be applied using SPSS.
  • APA in Focus sections explain how to summarize statistical results for each inferential statistic taught and how to read and report statistical results in research journals that follow APA style.
  • Research in Focus sections in Chapters 1 through 7 provide context by reviewing pertinent, current research that clarifies or illustrates important statistical concepts discussed in the chapter.
  • Current research examples, often based on data from published research, allow students to see the types of questions that behavioral researchers ask while learning about the statistics researchers use to answer them.
  • Learning Checks and Marginal Notes support a deeper understanding of the material.
  • Robust pedagogy, including step-by-step example problems, checkpoints for comprehension, bolded, boxed, and defined key terms, a comprehensive suite of end-of-chapter problems, and a mathematics primer in an appendix, help students master key concepts and skills.
  • Over 30 chapter-ending review problems, categorized as Factual Problems, Concept and Application Problems, and Problems in Research, allow instructors to easily identify and specifically test the type of knowledge they want to assess. 

 

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