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• Title Page
• Copyright Page
• Dedication
• About the Authors
• Contents
• Preface
• Acknowledgments
• Index of Applications
• Chapter 1: Introduction to Data
• Case Study: Deadly Cell Phones?
• 1.1. What Are Data?
• 1.2. Classifying and Storing Data
• 1.3. Organizing Categorical Data
• 1.4. Collecting Data to Understand Causality
• Exploring Statistics: Collecting a Table of Different Kinds of Data
• Chapter 2: Picturing Variation with Graphs
• Case Study: Student-to-Teacher Ratio at Colleges
• 2.1. Visualizing Variation in Numerical Data
• 2.2. Summarizing Important Features of a Numerical Distribution
• 2.3. Visualizing Variation in Categorical Variables
• 2.4. Summarizing Categorical Distributions
• 2.5. Interpreting Graphs
• Exploring Statistics: Personal Distance
• Chapter 3: Numerical Summaries of Center and Variation
• Case Study: Living in a Risky World
• 3.1. Summaries for Symmetric Distributions
• 3.2. What’s Unusual? The Empirical Rule and z-Scores
• 3.3. Summaries for Skewed Distributions
• 3.4. Comparing Measures of Center
• 3.5. Using Boxplots for Displaying Summaries
• Exploring Statistics: Does Reaction Distance Depend on Gender?
• Chapter 4: Regression Analysis: Exploring Associations between Variables
• Case Study: Catching Meter Thieves
• 4.1. Visualizing Variability with a Scatterplot
• 4.2. Measuring Strength of Association with Correlation
• 4.3. Modeling Linear Trends
• 4.4. Evaluating the Linear Model
• Exploring Statistics: Guessing the Age of Famous People
• Chapter 5: Modeling Variation with Probability
• Case Study: SIDS or Murder?
• 5.1. What Is Randomness?
• 5.2. Finding Theoretical Probabilities
• 5.3. Associations in Categorical Variables
• 5.4. Finding Empirical Probabilities
• Exploring Statistics: Let’s Make a Deal: Stay or Switch?
• Chapter 6: Modeling Random Events: The Normal and Binomial Models
• Case Study: You Sometimes Get More Than You Pay For
• 6.1. Probability Distributions Are Models of Random Experiments
• 6.2. The Normal Model
• 6.3. The Binomial Model (optional)
• Exploring Statistics: ESP with Coin Flipping
• Chapter 7: Survey Sampling and Inference
• Case Study: Spring Break Fever: Just What the Doctors Ordered?
• 7.1. Learning about the World through Surveys
• 7.2. Measuring the Quality of a Survey
• 7.3. The Central Limit Theorem for Sample Proportions
• 7.4. Estimating the Population Proportion with Confidence Intervals
• 7.5. Comparing Two Population Proportions with Confidence
• Exploring Statistics: Simple Random Sampling Prevents Bias
• Chapter 8: Hypothesis Testing for Population Proportions
• Case Study: Dodging the Question
• 8.1. The Essential Ingredients of Hypothesis Testing
• 8.2. Hypothesis Testing in Four Steps
• 8.3. Hypothesis Tests in Detail
• 8.4. Comparing Proportions from Two Populations
• Exploring Statistics: Identifying Flavors of Gum through Smell
• Chapter 9: Inferring Population Means
• Case Study: Epilepsy Drugs and Children
• 9.1. Sample Means of Random Samples
• 9.2. The Central Limit Theorem for Sample Means
• 9.3. Answering Questions about the Mean of a Population
• 9.4. Hypothesis Testing for Means
• 9.5. Comparing Two Population Means
• 9.6. Overview of Analyzing Means
• Exploring Statistics: Pulse Rates
• Chapter 10: Analyzing Categorical Variables and Interpreting Research
• Case Study: Popping Better Popcorn
• 10.1. The Basic Ingredients for Testing with Categorical Variables
• 10.2. Chi-Square Tests for Associations between Categorical Variables
• 10.3. Reading Research Papers
• Exploring Statistics: Skittles
• Appendix A: Tables
• Appendix B: Check Your Tech Answers
• Appendix C: Answers to Odd-Numbered Exercises
• Appendix D: Credits
• Index
• Back Cover