Linear Models in Statistics

Preface. 1. Introduction. 2. Matrix Algebra. 3. Random Vectors and Matrices. 4. Multivariate Normal Distribution. 5. Distribution of Quadratic Forms in y. 6. Simple Linear Regression. 7. Multiple Regression: Estimation. 8. Multiple Regression: tests of Hypotheses and Confidence Intervals. 9. Multiple Regression: Model Validation and Diagnostics. 10. Multiple Regression: random x’s. 11. Multiple Regression: Bayesian Inference. 12. Analysis-of-Variance Models. 13. One-Way Analysis-of-Variance: balanced Case. 14. Two-Way Analysis-of Variance: Balanced Case. 15. Analysis-of-Variance: The Cell Means Model for Unbalanced Data. 16. Analysis-of-Covariance. 17. Linear Mixed Models. 18. Additional Models. Appendix A. Answers and Hits to the Problems. References. Index.