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Applied Linear Regression Models (Kutner)

 Author(s)  Kutner, Nachtsheim, Neter
 Title  Applied Linear Regression Models
 Edition  Fourth Edition
 Year  2004
 Publisher  McGraw-Hill Irwin
 ISBN  0-07-301344-7

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

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