Solutions Manual to accompany Introduction to Linear Regression Analysis

Nonfiction, Science & Nature, Technology, Engineering, Industrial, Mathematics, Probability, Statistics
Cover of the book Solutions Manual to accompany Introduction to Linear Regression Analysis by Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining, Wiley
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Author: Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining ISBN: 9781118548509
Publisher: Wiley Publication: April 23, 2013
Imprint: Wiley Language: English
Author: Ann G. Ryan, Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining
ISBN: 9781118548509
Publisher: Wiley
Publication: April 23, 2013
Imprint: Wiley
Language: English

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.

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