Understanding Regression Analysis : A Conditional Distribution Approach (Paperback)

1. Introduction to Regression Models 2. Estimating Regression Model Parameters3. The Classical Model and Its Consequences4. Evaluating Assumptions5. Transformations6. The Multiple Regression Model7. Multiple Regression from the Matrix Point of View8. R-squared, Adjusted R-Squared, the F Test, and Multicollinearity9. Polynomial Models and Interaction (Moderator) Analysis10. ANOVA, ANCOVA, and Other Applications of Indicator Variables11. Variable Selection12. Heteroscedasticity and Non-independence13. Models for Binary,Nominal, and OrdinalResponse Variables14. Models for Poisson and Negative Binomial Response15. Censored Data Models16. Outliers, Identification, Problems, and Remedies (Good and Bad)17. Neural Network Regression 18. Regression Trees19. Bookend