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# Statistics for the Behavioral Sciences

Third Edition

- Gregory J. Privitera - St. Bonaventure University

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.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

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