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Statistics for the Behavioral Sciences

Statistics for the Behavioral Sciences

Third Edition
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July 2017 | 816 pages | SAGE Publications, Inc

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
Preface to the Instructor
To the Student—How to Use SPSS With This Book
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  
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  
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  
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  
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


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Key features


  • 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.
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  • An updated Student Study Guide also by Privitera provides even more opportunity for review, practice, and mastery of concepts.


  • 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. 


Sample Materials & Chapters

Chapter 1: Introduction to Statistics

Chapter 2- Summarizing Data

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