Statistics for the Behavioral Sciences

Part I: Introduction and Descriptive Statistics 
Chapter 1: Introduction to Statistics 
1.1 The Use of Statistics in Science 
1.2 Descriptive and Inferential Statistics 
1.3 Research Methods and Statistics 
1.4 Scales of Measurement 
1.5 Types of Data 
1.6 Research in Focus: Types of Data and Scales of Measurement 
1.7 SPSS in Focus: Entering and Defining Variables 
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 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 4: Summarizing Data: Variability 
4.1 Measuring Variability 
4.2 The Range 
4.3 Research in Focus: Reporting the Range 
4.4 Quartiles and Intequartiles 
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 
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’ 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 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 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 
Part III: Probability and the Foundations of Inferential Statistics 
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 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 10: Testing Means: Related Samples t Test 
10.1 Related and Independent Samples 
10.2 Introduction to the Related Samples t Test 
10.3 Related Samples t Test: Repeated-Measures Design 
10.4 SPSS in Focus: The Related Samples t Test 
10.5 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 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: Precisions and Certainty 
11.11: APA in Focus: Reporting Confidence Intervals 
Part IV: Making Inferences About the Variability of Two or More Means 
Chapter 12. Analysis of Variance: One-Way Between-Subjects Design 
12.1 Increasing k: A Shift to Analyzing Variance 
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 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 Comparison: 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 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 and Interactions 
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 
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 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 Measure 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 Beta 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 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 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 
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 
Appendix B: Statistical Tables 
Table B.1 The Unit Normal Table 
Table B.2 The t Distribution 
Table B.3 Critical Values for F Distribution 
Table B.4 The Studentized Range Statistic (q) 
Table B.5 Critical Values for the Pearson Correlation 
Table B.6 Critical Values for the Spearman Correlation 
Table B.7 Critical Values of Chi-Square 
Table B.8 Distribution of Binomial Probabilities 
Table B.9 Wilcoxon Signed-Rank T Critical Values 
Table B.10 Critical Values of the Mann-Whitney U 
Appendix C: Chapter Solutions for Even-Numbered Problems