## Table of contents

**1 Statistical Reasoning: Investigating a Claim of Discrimination.**

1.1 Discrimination in the Workplace: Data Exploration.

1.2 Discrimination in the Workplace: Inference.

Chapter Summary.

**2 Exploring Distributions of Data.**

2.1 Visualizing Distributions: Shape, Center, and Spread.

2.2 Summarizing Center and Spread.

2.3 Working with Summary Statistics.

2.4 The Normal Distribution.

Chapter Summary.

**3 Relationship between Two Quantitative Variables.**

3.1 Scatterplots.

3.2 Regression: Getting a Line on the Pattern.

3.3 Correlation: The Strength of a Linear Trend.

3.4 Diagnostics: Looking for Features That the Summaries Miss.

Chapter Summary.

**4 Sample Surveys and Experiments.**

4.1 Random Sampling: Playing It Safe by Taking Chances.

4.2 Why Take Samples, and How Not To.

4.3 Experiments and Inference about Cause.

4.4 Designing Experiments to Reduce Variability.

Chapter Summary.

**5 Probability Models.**

5.1 Models of Random Behavior.

5.2 The Addition Rule and Disjoint Events.

5.3 Conditional Probability and the Multiplication Rule.

5.4 Independent Events.

Chapter Summary.

**6 Probability Distributions.**

6.1 Probability Distributions and Expected Value.

6.2 Rules for Means and Variances of Probability Distributions.

6.3 The Binomial Distribution.

Chapter Summary.

**7 Sampling Distributions.**

7.1 Generating Sampling Distributions.

7.2 Sampling Distribution of the Sample Mean.

7.3 Sampling Distribution of the Sample Proportion.

Chapter Summary.

**8 Inference for a Proportion.**

8.1 A Confidence Interval for a Proportion.

8.2 A Significance Test for a Proportion: Interpreting a P-Value.

8.3 A Significance Test for a Proportion: Making a Decision.

8.4 Types of Errors and Power of a Test.

Chapter Summary.

**9 Comparing Two Populations: Inference for the Difference of Two Proportions.**

9.1 A Confidence Interval for the Difference of Two Proportions.

9.2 A Significance Test for the Difference of Two Proportions.

9.3 Inference for Experiments and Observational Studies.

Chapter Summary.

**10 Inference for Means.**

10.1 A Confidence Interval for a Mean.

10.2 A Significance Test for a Mean: Interpreting a P-Value.

10.3 Fixed-Level Tests.

Chapter Summary.

**11 Comparing Two Populations: Inference for the Difference of Two Means.**

11.1 A Confidence Interval for the Difference of Two Means.

11.2 A Significance Test for the Difference of Two Means.

11.3 Inference for Paired Comparisons.

Chapter Summary.

**12 Chi-Square Tests.**

12.1 Testing a Probability Model: The Chi-Square Goodness-of-Fit Test.

12.2 The Chi-Square Test of Homogeneity.

12.3 The Chi-Square Test of Independence.

Chapter Summary.

**13 Inference for Regression.**

13.1 Variation in the Slope from Sample to Sample.

13.2 Making Inferences about Slopes.

Chapter Summary.

**14 One- Way Analysis of Variance.**

14.1 A New Look at the Two-Sample t-Test.

14.2 One-Way ANOVA: When There Are More Than Two Groups.

Chapter Summary.

**15 Multiple Regression.**

15.1 From One to Two Explanatory Variables.

15.2 From Two to More Explanatory Variables, including Categorical

Variables.

Chapter Summary.

16 *Martin vs. Westvaco Revisited: Testing for Possible Discrimination in the Workplace.*

Table A: Standard Normal Probabilities.

Table B: t-Distribution Critical Values.

Table C: x2 Critical Values.

Table D: F-Distribution Critical Values for α=0.05.

Table E: Random Digits.

Glossary.

Brief Answers to Practice Problems and Selected Exercises.