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9781119578727: Introduction to Linear Regression Analysis (Wiley Series in Probability and Statistics)

Synopsis

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.

    From the Back Cover

    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.

    From the Inside Flap

    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.

    "About this title" may belong to another edition of this title.

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