MP Applied Linear Regression Models-Revised Edition with Student CD

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  • Edition: 4th
  • Format: Hardcover w/CD
  • Copyright: 2004-01-08
  • Publisher: McGraw-Hill Education

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Thoroughly updated and more straightforward than ever,Applied Linear Regression Modelsincludes the latest statistics, developments, and methods in multicategory logistic regression; expanded treatment of diagnostics for logistic regression; a more powerful Levene test; and more. Cases, datasets, and examples allow for a more real-world perspective and explore relevant uses of regression techniques in business today.

Author Biography

Michael H. Kutner is a professor at Emory University in Atlanta.

Chris J. Nachtsheim is a professor at the University of Minnesota--Minneapolis.

John Neter is a professor at the University of Georgia in Athens.

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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