Douglas C. Montgomery & Elizabeth A. Peck 
Introduction to Linear Regression Analysis [EPUB ebook] 

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INTRODUCTION TO LINEAR REGRESSION ANALYSIS
A comprehensive and current introduction to the fundamentals of regression analysis
Introduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.
The new edition focuses on four key areas of improvement over the fifth edition:
* New exercises and data sets
* New material on generalized regression techniques
* The inclusion of JMP software in key areas
* Carefully condensing the text where possible
Introduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today’s cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.

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About the author

DOUGLAS C. MONTGOMERY, PHD, is Regents Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery is the co-author of several Wiley books including Introduction to Linear Regression Analysis, 5th Edition.
ELIZABETH A. PECK, PHD, is Logistics Modeling Specialist at the Coca-Cola Company in Atlanta, Georgia.
G. GEOFFREY VINING, PHD, is Professor in the Department of Statistics at Virginia Polytechnic and State University. Dr. Peck is co-author of Introduction to Linear Regression Analysis, 5th Edition.

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Language English ● Format EPUB ● Pages 704 ● ISBN 9781119578758 ● File size 49.0 MB ● Publisher John Wiley & Sons ● Published 2021 ● Edition 6 ● Downloadable 24 months ● Currency EUR ● ID 7767062 ● Copy protection Adobe DRM
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