- The authors efficiently use mathematics as a necessary tool to promote a firm understanding of statistical techniques.
- Stressing connectivity, the authors explain not only how major topics play a role in statistical inference but also how the topics are related to one another. These integrating discussions appear most frequently in chapter introductions and conclusions.
- This text takes a practical approach in both the exercises throughout and the useful topics in statistical methodology covered in the last five chapters.
- Exercises are based on real data or actual experimental scenarios which allow students to see the practical uses of various statistical and probabilistic methods.
3. Discrete Random Variables and Their Probability Distributions.
4. Continuous Random Variables and Their Probability Distributions.
5. Multivariate Probability Distributions.
6. Functions of Random Variables.
7. Sampling Distributions and the Central Limit Theorem.
9. Properties of Point Estimators and Methods of Estimation.
10. Hypothesis Testing.
11. Linear Models and Estimation by Least Squares.
12. Considerations in Designing Experiments.
13. The Analysis of Variance.
14. Analysis of Categorical Data.
15. Nonparametric Statistics.
16. Introduction to Bayesian Methods for Inference.
Appendix 1. Matrices and Other Useful Mathematical Results.
Appendix 2. Common Probability Distributions, Means, Variances, and Moment-Generating Functions.
Appendix 3. Tables. Binomial Probabilities.
Dennis Wackerly / Richard L. Scheaffer/ William Mendenhall
0495110817 | 9780495110811