Statistics: Unlocking the Power of Data

Chapter 1: Collecting Data

• • 1.1. The Structure of Data
• • 1.2. Sampling from a Population
• • 1.3. Experiments and Observational Studies

Chapter 2: Describing Data

• • 2.1. Categorical Variables
• • 2.2. One Quantitative Variable: Shape and Center
• • 2.3. One Quantitative Variable: Measures of Spread
• • 2.4. Boxplots and Quantitative/Categorical Relationships
• • 2.5. Two Quantitative Variables: Scatterplot and Correlation
• • 2.6. Two Quantitative Variables: Linear Regression
• • 2.7. Data Visualization and Multiple Variables

Chapter 3: Confidence Intervals

• • 3.1. Sampling Distributions
• • 3.2. Understanding and Interpreting Confidence Intervals
• • 3.3. Constructing Bootstrap Confidence Intervals
• • 3.4. Bootstrap Confidence Intervals using Percentiles

Chapter 4: Hypothesis Tests

• • 4.1. Introducing Hypothesis Tests
• • 4.2. Measuring Evidence with P-values
• • 4.3. Determining Statistical Significance
• • 4.4. A Closer Look at Testing
• • 4.5. Making Connections

Chapter 5: Approximating with a Distribution

• • 5.1. Hypothesis Tests Using Normal Distributions
• • 5.2. Confidence Intervals Using Normal Distributions

Chapter 6: Inference for Means and Proportions

• • 6.1. Inference for a Proportion
• • 6.1-D Distribution of a Proportion
• • 6.1-CI Confidence Interval for a Proportion
• • 6.1-HT Hypothesis Test for a Proportion
• • 6.2. Inference for a Mean
• • 6.2-D Distribution of a Mean
• • 6.2-CI Confidence Interval for a Mean
• • 6.2-HT Hypothesis Test for a Mean
• • 6.3. Inference for a Difference in Proportions
• • 6.3-D Distribution of a Difference in Proportions
• • 6.3-CI Confidence Interval for a Difference in Proportions
• • 6.3-HT Hypothesis Test for a Difference in Proportions
• • 6.4. Inference for a Difference in Means
• • 6.4-D Distribution of a Difference in Means
• • 6.4-CI Confidence Interval for a Difference in Means
• • 6.4-HT Hypothesis Test for a Difference in Means
• • 6.5. Paired Difference in Means

Chapter 7: Chi-Square Tests for Categorical Variables

• • 7.1. Testing Goodness-of-Fit for a Single Categorical Variable
• • 7.2. Testing for an Association between Two Categorical Variables

Chapter 8: ANOVA to Compare Means

• • 8.1. Analysis of Variance
• • 8.2. Pairwise Comparisons and Inference after ANOVA

Chapter 9: Inference for Regression

• • 9.1. Inference for Slope and Correlation
• • 9.2. ANOVA for Regression
• • 9.3. Confidence and Prediction Intervals

Chapter 10: Multiple Regression

• • 10.1. Multiple Predictors
• • 10.2. Checking Conditions for a Regression Model
• • 10.3. Using Multiple Regression

Chapter P: Probability Basics

• • P.1. Probability Rules
• • P.2. Tree Diagrams and Bayes’ Rule
• • P.3. Random Variables and Probability Functions
• • P.4. Binomial Probabilities
• • P.5. Density Curves and the Normal Distribution

Chapter Appendix A: Chapter Summaries

Chapter Appendix B: Selected Dataset Descriptions