Introduction 1 Part 1: Getting Started with Statistical Analysis with Python 7 Chapter 1: Data, Statistics, and Decisions 9 Chapter 2: Python: What It Does and How It Does It 17 Part 2: Describing Data 45 Chapter 3: Getting Graphic 47 Chapter 4: Finding Your Center 61 Chapter 5: Deviating from the Average 73 Chapter 6: Meeting Standards and Standings 83 Chapter 7: Summarizing It All 93 Chapter 8: What's Normal? 105 Part 3: Drawing Conclusions from Data 121 Chapter 9: The Confidence Game: Estimation 123 Chapter 10: One-Sample Hypothesis Testing 137 Chapter 11: Two-Sample Hypothesis Testing 159 Chapter 12: Testing More than Two Samples 181 Chapter 13: More Complicated Testing 211 Chapter 14: Regression: Linear, Multiple, and the General Linear Model 233 Chapter 15: Correlation: The Rise and Fall of Relationships 273 Chapter 16: Curvilinear Regression: When Relationships Get Complicated 289 Part 4: Working with Probability 317 Chapter 17: Introducing Probability 319 Chapter 18: Introducing Modeling 341 Chapter 19: Probability Meets Regression: Logistic Regression 363 Part 5: The Part of Tens 373 Chapter 20: Ten Tips for R Veterans 375 Chapter 21: Ten Valuable Python Resources 383 Index 387.