Regression Analysis

Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.

Examples and exercises contain real data and graphical illustration for ease of interpretationOutputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statistical software package will work equally well

1. The Analysis of Means: A Review of Basics and an Introduction to Linear Models 2. Simple Linear Regression:Linear Regression with One Independent Variable 3. Multiple Regression 4. Problems with Observations 5. Multicollinearity 6. Problems with the Model 7. Curve Fitting 8. Introduction to Nonlinear Models 9. Indicator Variables 10. Categorical Response Variables 11. Generalized Linear Models

Appendix A: Statistical Tables B: A Brief Introduction to Matrices C: Estimation Procedures