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