I: GATHERING AND EXPLORING DATA 1. Statistics: The Art and Science of Learning From Data 1.1 Using Data to Answer Statistical Questions 1.2 Sample Versus Population 1.3 Organizing Data, Statistical Software, and the New Field of Data Science Chapter Summary Chapter Exercises 2. Exploring Data With Graphs and Numerical Summaries 2.1 Different Types of Data 2.2 Graphical Summaries of Data 2.3 Measuring the Center of Quantitative Data 2.4 Measuring the Variability of Quantitative Data 2.5 Using Measures of Position to Describe Variability 2.6 Linear Transformations and Standardizing 2.7 Recognizing and Avoiding Misuses of Graphical Summaries Chapter Summary Chapter Exercises 3. Exploring Relationships Between Two Variables 3.1 The Association Between Two Categorical Variables 3.2 The Relationship Between Two Quantitative Variables 3.3 Linear Regression: Predicting the Outcome of a Variable 3.4 Cautions in Analyzing Associations Chapter Summary Chapter Exercises 4. Gathering Data 4.1 Experimental and Observational Studies 4.2 Good and Poor Ways to Sample 4.3 Good and Poor Ways to Experiment 4.4 Other Ways to Conduct Experimental and Nonexperimental Studies Chapter Summary Chapter Exercises II: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLINGDISTRIBUTIONS 5. Probability in Our Daily Lives 5.1 How Probability Quantifies Randomness 5.2 Finding Probabilities 5.3 Conditional Probability 5.4 Applying the Probability Rules Chapter Summary Chapter Exercises 6. Random Variables and Probability Distributions 6.1 Summarizing Possible Outcomes and Their Probabilities 6.2 Probabilities for Bell-Shaped Distributions 6.3 Probabilities When Each Observation Has Two Possible Outcomes Chapter Summary Chapter Exercises 7. Sampling Distributions 7.1 How Sample Proportions Vary Around the Population Proportion 7.2 How Sample Means Vary Around the Population Mean 7.3 Using the Bootstrap to Find Sampling Distributions Chapter Summary Chapter Exercises III: INFERENTIAL STATISTICS 8. Statistical Inference: Confidence Intervals 8.1 Point and Interval Estimates of Population Parameters 8.2 Confidence Interval for a Population Proportion 8.3 Confidence Interval for a Population Mean 8.4 Bootstrap Confidence Intervals Chapter Summary Chapter Exercises 9. Statistical Inference: Significance Tests About Hypotheses 9.1 Steps for Performing a Significance Test 9.2 Significance Tests About Proportions 9.3 Significance Tests About a Mean 9.4 Decisions and Types of Errors in Significance Tests 9.5 Limitations of Significance Tests 9.6 The Likelihood of a Type II Error Chapter Summary Chapter Exercises 10. Comparing Two Groups 10.1 Categorical Response: Comparing Two Proportions 10.2 Quantitative Response: Comparing Two Means 10.3 Comparing Two Groups with Bootstrap or Permutation Resampling 10.4 Analyzing Dependent Samples 10.5 Adjusting for the Effects of Other Variables Chapter Summary Chapter Exercises IV: ANALYZING ASSOCIATION AND EXTENDED STATISTICALMETHODS 11. Analyzing the Association Between Categorical Variables 11.1 Independence and Dependence (Association) 11.2 Testing Categorical Variables for Independence 11.3 Determining the Strength of the Association 11.4 Using Residuals to Reveal the Pattern of Association 11.5 Fisher's Exact and Permutation Tests Chapter Summary Chapter Exercises 12. Analyzing the Association Between Quantitative Variables: Regression Analysis 12.1 Modeling How Two Variables Are Related 12.2 Inference About Model Parameters and the Association 12.3 Describing the Strength of Association 12.4 How the Data Vary Around the Regression Line 12.5 Exponential Regression: A Model for Nonlinearity Chapter Summary Chapter Exercises 13. Multiple Regression 13.1 Using Several Variables to Predict a Response 13.2 Extending the Correlation and R2 for Multiple Regression 13.3 Using Multiple Regression to Make Inferences 13.4 Checking a Regression Model Using Residual Plots 13.5 Regression and Categorical Predictors 13.6 Modeling a Categorical Response Chapter Summary Chapter Exercises 14. Comparing Groups: Analysis of Variance Methods 14.1 One-Way ANOVA: Comparing Several Means 14.2 Estimating Differences in Groups for a Single Factor 14.3 Two-Way ANOVA 14.4 Chapter Summary Chapter Exercises 15. Nonparametric Statistics 15.1 Compare Two Groups by Ranking 15.2 Nonparametric Methods for Several Groups and for Matched Pairs Chapter Summary Chapter Exercises Appendix Answers Index Index of Applications Credits