Applied Linear Regression Models (Kutner)
Table of Contents
Part1 Simple Linear Regression
1 Linear Regression with One Predictor Variable
2 Inferences in Regression and Correlation Analysis
3 Diagnostics and Remedial Measures
4 Simultaneous Inferences and Other Topics in Regression Analysis
5 Matrix Approach to Simple Linear Regression Analysis
Part 2 Multiple Linear Regression
6 Multiple Regression I
7 Multiple Regression II
8 Building the Regression Model I: Models for Quantitative and Qualitative Predictors
9 Building the Regression Model II: Model Selection and Validation
10 Building the Regression Model III: Diagnostics
11 Remedial Measures and Alternative Regression Techniques
12 Autocorrelation in Time Series Data
Part 3 Nonlinear Regression
13 Introduction to Nonlinear Regression and Neural Networks
14 Logistic Regression, Poisson Regression, and Generalized Linear Models