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• Title Page
• Copyright
• Dedication
• Contents
• An Introduction to the Web Apps
• Preface
• About the Authors
• Part One: Gathering and Exploring Data
• Chapter 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
• Chapter 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
• Chapter 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
• Chapter 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
• Part Two: Probability, Probability Distributions, and Sampling Distributions
• Chapter 5. Probability in Our DailyLives
• 5.1 How Probability Quantifies Randomness
• 5.2 Finding Probabilities
• 5.3 Conditional Probability
• 5.4 Applying the Probability Rules
• Chapter Summary
• Chapter Exercises
• Chapter 6. Random Variables and Probability Distributions
• 6.1 Summarizing Possible Outcomes and Their Probabilities
• 6.2 Probabilities for Bell-Shaped Distributions: The Normal Distribution
• 6.3 Probabilities When Each Observation Has Two Possible Outcomes: The Binomial Distribution
• Chapter Summary
• Chapter Exercises
• Chapter 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
• Part Three: Inferential Statistics
• Chapter 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
• Chapter 9. Statistical Inference: Significance Tests About Hypotheses
• 9.1 Steps for Performing a Significance Test
• 9.2 Significance Test About a Proportion
• 9.3 Significance Test 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 and the Power of a Test
• Chapter Summary
• Chapter Exercises
• Chapter 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
• Part Four: Extended Statistical Methods and Models for Analyzing Categorical and Quantitative Variab
• Chapter 11. Categorical Data Analysis
• 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
• Chapter 12. Regression Analysis
• 12.1 The Linear Regression Model
• 12.2 Inference About Model Parameters and the Relationship
• 12.3 Describing the Strength of the Relationship
• 12.4 How the Data Vary Around the Regression Line
• 12.5 Exponential Regression: A Model for Nonlinearity
• Chapter Summary
• Chapter Exercises
• Chapter 13. Multiple Regression
• 13.1 Using Several Variables to Predict a Response
• 13.2 Extending the Correlation Coefficient and R2 for Multiple Regression
• 13.3 Inferences Using Multiple Regression
• 13.4 Checking a Regression Model Using Residual Plots
• 13.5 Regression and Categorical Predictors
• 13.6 Modeling a Categorical Response: Logistic Regression
• Chapter Summary
• Chapter Exercises
• Chapter 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: Exploring Two Factors and Their Interaction
• Chapter Summary
• Chapter Exercises
• Chapter 15. Nonparametric Statistics
• 15.1 Compare Two Groups by Ranking
• 15.2 Nonparametric Methods for Several Groups and for Dependent Samples
• Chapter Summary
• Chapter Exercises
• Appendix
• Answers
• Index
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• X
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• Z
• Index of Applications
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• Credits