Chapter 1 Introduction Chapter 2 Estimation Chapter 3 Inference Chapter 4 Errors in Predictors Chapter 5 Generalized Least Squares Chapter 6 Testing for Lack of Fit Chapter 7 Diagnostics Chapter 8 Transformation Chapter 9 Scale Changes, Principal Components and Collinearity Chapter 10 Variable Selection Chapter 11 Statistical Strategy and Model Uncertainty Chapter 12 Chicago Insurance Redlining - a complete example Chapter 13 Robust and Resistant Regression Chapter 14 Missing Data Chapter 15 Analysis of Covariance Chapter 16 ANOVA
