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Introduction to Regression Analysis

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This book is an introduction to regression analysis for upper division and graduate students in science, engineering, social science and medicine. The emphasis is on the classical linear regression diagnostics, ridge and logistic regression are treated as well. In contrast to other books at this level, the theoretical foundation of the subject is presented in some detail based on extensive use of matrix algebra. throughout the text, model building and evaluation are emphasized and illustrated with many numerical examples.

Author(s): Michael A. Golberg, Hokwon A. Cho
Edition: 2
Publisher: WIT Press
Year: 2010

Language: English
Pages: 452

Contents
Preface
1 Introduction
2 Some Basic Results in Probability and Statistics
3 Simple Linear Regression
4 Random Vectors and Matrix Algebra
5 Multiple Regression
6 Residuals, Diagnostics and Transformations
7 Further Applications of Regression Techniques
8 Selection of a Regression Model
9 Multicollinearity: Diagnosis and Remedies
Appendix
Bibliography
Index