What is Statistics?
PART I. ANALYZING DATA: LOOKING FOR PATTERNS AND DEPARTURES FROM PATTERNS
1. Exploring Data
1.1 Displaying Distributions with Graphs
1.2 Describing Distributions with Numbers
2. Describing Location in Distribution
2.1 Measures of Relative Standing and Density Curves
2.2 Normal Distributions
3. Examining Relationships
3.1 Scatterplots and Correlation
3.2 Least-Squares Regression
3.3 Correlation and Regression Wisdom
4. More about Relationships between Two Variables
4.1 Transforming to Achieve Linearity
4.2 Relations in Categorical Data
4.3 Establishing Causation
PART II. PRODUCING DATA: SURVEYS, OBSERVATIONAL STUDIES, AND EXPERIMENTS
5. Producing Data
5.1 Designing Samples
5.2 Designing Experiments
PART III PROBABILITY AND RANDOM VARIABLES: FOUNDATIONS OF INFERENCE
6. Probability and Simulation: The Study of Randomness
6.1 Simulation
6.2 Probability Models
6.3 General Probability Rules
7. Random Variables
7.1 Discrete and Continuous Random Variables
7.2 Means and Variances of Random Variables
8. The Binomial and Geometric Distributions
8.1 The Binomial Distributions
8.2 The Geometric Distributions
9. Sampling Distributions
9.1 Sampling Distributions
9.2 Sample Proportions
9.3 Sample Means
PART IV. INFERENCE: CONCLUSIONS WITH CONFIDENCE
10. Estimating with Confidence
10.1 Confidence Intervals: The Basics
10.2 Estimating a Population Mean
10.3 Estimating a Population Proportion
11. Testing a Claim
11.1 Significance Tests: The Basics
11.2 Carrying Out Significance Tests
11.3 Use and Abuse of Tests
11.4 Using Inference to Make Decisions
12. Significance Tests in Practice
12.1 Tests about a Population Mean
12.2 Tests about a Population Proportion
13. Comparing Two Population Parameters
13.1 Comparing Two Means
13.2 Comparing Two Proportions
14. Inference for Distributions of Categorical Variables: Chi-Square Procedures
14.1 Test for Goodness of Fit
14.2 Inference for Two-Way Tables
15. Inference for Regression
Additional Chapters on CD-ROM or at the Practice of Statistics Companion Web Site:
A. Analysis of Variance
B. Multiple Linear Regression: A Case Study
C. Logistic Regression: A Case Study
15.1 Inference for Population Spread
15.2 One-Way Analysis of Variance
Additional, optional, post-exam chapters on the student and instructor's CDs:
16. Multiple Linear Regression
17. Logistic Regression