# Introduction to Linear Regression Analysis, 5th Edition

## Book Description

**Praise for the Fourth Edition**

"As with previous editions, the authors have produced a leading textbook on regression."

—*Journal of the American Statistical Association*

**A comprehensive and up-to-date introduction to** **the fundamentals of regression analysis**

*Introduction to Linear Regression Analysis, Fifth Edition* continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.

Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The *Fifth Edition* features numerous newly added topics, including:

- A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models
- Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model
- Tests on individual regression coefficients and subsets of coefficients
- Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data.

In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material.

*Introduction to Linear Regression Analysis, Fifth Edition* is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.

### Table of Contents

Chapter 1. Introduction

Chapter 2. Simple Linear Regression

Chapter 3. Multiple Linear Regression

Chapter 4. Model Adequacy Checking

Chapter 5. Transformations And Weighting To Correct Model Inadequacies

Chapter 6. Diagnostics For Leverage And Influence

Chapter 7. Polynomial Regression Models

Chapter 8. Indicator Variables

Chapter 9. Multicollinearity

Chapter 10. Variable Selection And Model Building

Chapter 11. Validation Of Regression Models

Chapter 12. Introduction To Nonlinear Regression

Chapter 13. Generalized Linear Models

Chapter 14. Regression Analysis Of Time Series Data

Chapter 15. Other Topics In The Use Of Regression Analysis

Appendix A Statistical Tables

Appendix B Data Sets For Exercises

Appendix C Engine Displacement.

Appendix D Introduction To Sas

## Book Details

- Title: Introduction to Linear Regression Analysis, 5th Edition
- Author: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
- Length: 672 pages
- Edition: 5
- Language: English
- Publisher: Wiley
- Publication Date: 2012-04-09
- ISBN-10: 0470542810
- ISBN-13: 9780470542811

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