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 MAKING SENSE-Populations and Samples 1.3 Research Methods and Statistics MAKING SENSE-Experimental and Control Groups 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 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 Graphing Distributions: Continuous Data 2.

9 Graphing Distributions: Discrete and Categorical Data MAKING SENSE- Deception Due to the Distortion of Data 2.10 Research in Focus: Frequencies and Percents 2.11 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 MAKING SENSE-Making the Grade 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 and Interquartile Range 4.3 Research in Focus: Reporting the Range 4.4 The Variance 4.5 Explaining Variance for Populations and Samples 4.6 The Computational Formula for Variance 4.7 The Standard Deviation 4.

8 What Does the Standard Deviation Tell Us? MAKING SENSE-Standard Deviation and Nonnormal Distributions 4.9 Characteristics of the Standard Deviation 4.10 SPSS in Focus: Range, Variance, and Standard Deviation PART II: Probability and the Foundations of Inferential Statistics Chapter 5: Probability, Normal Distributions, and z Scores 5.1 Introduction to Probability 5.2 Calculating Probability 5.3 Probability and the Normal Distribution 5.4 Characteristics of the Normal Distribution 5.5 Research in Focus: The Statistical Norm 5.

6 The Standard Normal Distribution and z Scores 5.7 A Brief Introduction to the Unit Normal Table 5.8 Locating Proportions 5.9 Locating Scores MAKING SENSE-Standard Deviation and the Normal Distribution 5.10 SPSS in Focus: Converting Raw Scores to Standard z Scores Chapter 6: Characteristics of the Sample Mean 6.1 Selecting Samples From Populations 6.2 Selecting a Sample: Who''s In and Who''s Out? 6.3 Sampling Distributions: The Mean 6.

4 The Standard Error of the Mean 6.5 Factors That Decrease Standard Error 6.6 SPSS in Focus: Estimating the Standard Error of the Mean 6.7 APA in Focus: Reporting the Standard Error 6.8 Standard Normal Transformations With Sampling Distributions Chapter 7: Hypothesis Testing: Significance, Effect Size, and Power 7.1 Inferential Statistics and Hypothesis Testing 7.2 Four Steps to Hypothesis Testing MAKING SENSE-Testing the Null Hypothesis 7.3 Hypothesis Testing and Sampling Distributions 7.

4 Making a Decision: Types of Error 7.5 Testing for Significance: Examples Using the z Test 7.6 Research in Focus: Directional Versus Nondirectional Tests 7.7 Measuring the Size of an Effect: Cohen''s d 7.8 Effect Size, Power, and Sample Size 7.9 Additional Factors That Increase Power 7.10 SPSS in Focus: A Preview for Chapters 8 to 14 7.11 APA in Focus: Reporting the Test Statistic and Effect Size PART III: Making Inferences About One or Two Means Chapter 8: Testing Means: One-Sample t Test With Confidence Intervals 8.

1 Going From z to t 8.2 The Degrees of Freedom 8.3 Reading the t Table 8.4 Computing the One-Sample t Test 8.5 Effect Size for the One- Sample t Test 8.6 Confidence Intervals for the One-Sample t Test 8.7 Inferring Significance and Effect Size From a Confidence Interval 8.8 SPSS in Focus: One-Sample t Test and Confidence Intervals 8.

9 APA in Focus: Reporting the t Statistic and Confidence Intervals Chapter 9: Testing Means: Two-Independent-Sample t Test With Confidence Intervals 9.1 Introduction to the Between- Subjects Design 9.2 Selecting Samples for Comparing Two Groups 9.3 Variability and Comparing Differences Between Two Groups 9.4 Computing the Two-Independent-Sample t Test MAKING SENSE-The Pooled Sample Variance 9.5 Effect Size for the Two-Independent-Sample t Test 9.6 Confidence Intervals for the Two-Independent-Sample t Test 9.7 Inferring Significance and Effect Size From a Confidence Interval 9.

8 SPSS in Focus: Two-Independent- Sample t Test and Confidence Intervals 9.9 APA in Focus: Reporting the t Statistic and Confidence Intervals Chapter 10: Testing Means: Related-Samples t Test With Confidence Intervals 10.1 Related Samples Designs 10.2 Introduction to the Related-Samples t Test 10.3 Computing the Related-Samples t Test MAKING SENSE-Increasing Power by Reducing Error 10.4 Measuring Effect Size for the Related-Samples t Test 10.5 Confidence Intervals for the Related-Samples t Test 10.6 Inferring Significance and Effect Size From a Confidence Interval 10.

7 SPSS in Focus: Related-Samples t Test and Confidence Intervals 10.8 APA in Focus: Reporting the t Statistic and Confidence Intervals PART IV: Making Inferences About The Variability of Two or More Means Chapter 11: One-Way Analysis of Variance: Between-Subjects and Within-Subjects (Repeated-Measures) Designs 11.1 An Introduction to Analysis of Variance 11.2 The Between-Subjects Design for Analysis of Variance 11.3 Computing the One-Way Between-Subjects ANOVA MAKING SENSE-Mean Squares and Variance 11.4 Post Hoc Tests: An Example Using Tukey''s HSD 11.5 SPSS in Focus: The One-Way Between-Subjects ANOVA 11.6 The Within-Subjects Design for Analysis of Variance 11.

7 Computing the One-Way Within-Subjects ANOVA 11.8 Post Hoc Tests for the Within-Subjects Design 11.9 SPSS in Focus: The One-Way Within-Subjects ANOVA 11.10 A Comparison of Within-Subjects and Between-Subjects Designs for ANOVA: Implications for Power 11.11 APA in Focus: Reporting the Results of the One-Way ANOVAs 327 Chapter Summary Organized by Learning Objective Chapter 12: Two-Way Analysis of Variance: Between- Subjects Factorial Design 12.1 Introduction to Factorial Designs 12.2 Structure and Notation for the Two-Way ANOVA 12.3 Describing Variability: Main Effects and Interactions MAKING SENSE-Graphing Interactions 12.

4 Computing the Two-Way Between-Subjects ANOVA 12.5 Analyzing Main Effects and Interactions 12.6 Measuring Effect Size for Main Effects and the Interaction 12.7 SPSS in Focus: The Two-Way Between-Subjects ANOVA 12.8 APA in Focus: Reporting the Results of the Two-Way ANOVAs PART V: Making Inferences About Patterns, Prediction, and Nonparametric Tests Chapter 13: Correlation and Linear Regression 13.1 The Structure of Data Used for Identifying Patterns and Making Predictions 13.2 Fundamentals of the Correlation 13.3 The Pearson Correlation Coefficient MAKING SENSE-Understanding Covariance 13.

4 SPSS in Focus: Pearson Correlation Coefficient 13.5 Assumptions and Limitations for Linear Correlations 13.6 Alternatives to Pearson: Spearman, Point-Biserial, and Phi 13.7 SPSS in Focus: Computing the Alternatives to Pearson 13.8 Fundamentals of Linear Regression 13.9 Using the Method of Least Squares to Find the Regression Line MAKING SENSE-SP, SS, and the Slope of a Regression Line 13.10 Using Analysis of Regression to Determine Significance 13.11 SPSS in Focus: Analysis of Regression 13.

12 A Look Ahead to Multiple Regression 13.13 APA in Focus: Reporting Correlations and Linear Regression Chapter 14: Chi-Square Tests: Goodness-of-Fit and the Test for Independence 14.1 Distinguishing Parametric and Nonparametric Tests 14.2 The Chi-Square Goodness-of-Fit Test MAKING SENSE-The Relative Size of a Discrepancy 14.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test 14.4 Interpreting the Chi-Square Goodness-of-Fit Test 14.5 The Chi-Square Test for Independence 14.6 Measures of Effect Size for the Chi-Square Test for Independence 14.

7 SPSS in Focus: The Chi-Square Test for Independence 14.8 APA in Focus: Reporting the Chi-Square Tests.