Douglas C. Montgomery & Elizabeth A. Peck 
Introduction to Linear Regression Analysis [PDF 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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Despre autor

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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Limba Engleză ● Format PDF ● Pagini 704 ● ISBN 9781119578741 ● Mărime fișier 18.1 MB ● Editura John Wiley & Sons ● Publicat 2021 ● Ediție 6 ● Descărcabil 24 luni ● Valută EUR ● ID 7750493 ● Protecție împotriva copiilor Adobe DRM
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