9780470542811-0470542810-Introduction to Linear Regression Analysis

Introduction to Linear Regression Analysis

ISBN-13: 9780470542811
ISBN-10: 0470542810
Edition: 5
Author: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
Publication date: 2012
Publisher: John Wiley & Sons Inc
Format: Hardcover 645 pages
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Book details

ISBN-13: 9780470542811
ISBN-10: 0470542810
Edition: 5
Author: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
Publication date: 2012
Publisher: John Wiley & Sons Inc
Format: Hardcover 645 pages

Summary

Introduction to Linear Regression Analysis (ISBN-13: 9780470542811 and ISBN-10: 0470542810), written by authors Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining, was published by John Wiley & Sons Inc in 2012. With an overall rating of 4.4 stars, it's a notable title among other Industrial, Manufacturing & Operational Systems (Engineering) books. You can easily purchase or rent Introduction to Linear Regression Analysis (Hardcover) from BooksRun, along with many other new and used Industrial, Manufacturing & Operational Systems books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $19.73.

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.

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