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Linear Regression Analysis: 330 (Wiley Series in Probability and Statistics) - Hardcover

 
9780471415404: Linear Regression Analysis: 330 (Wiley Series in Probability and Statistics)

Synopsis

Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
* This revision has been extensively class-tested.

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

About the Author

GEORGE A. F. SEBER, PhD, is Professor Emeritus of Statistics at the University of Auckland, New Zealand.

ALAN J. LEE, PhD, is the Chairman of the Department of Statistics at the University of Auckland.

From the Back Cover

An extensive treatment of a key method in the statistician s toolbox

For more than two decades, the First Edition of Linear Regression Analysis has been an authoritative resource for one of the most common methods of handling statistical data. There have been many advances in the field over the last twenty years, including the development of more efficient and accurate regression computer programs, new ways of fitting regressions, and new methods of model selection and prediction. Linear Regression Analysis, Second Edition, revises and expands this standard text, providing extensive coverage of state-of-the-art theory and applications of linear regression analysis.

Requiring no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models, this new edition features:

  • Up-to-date accounts of computational methods and algorithms currently in use without getting entrenched in minor computing details
  • A careful and detailed survey of the research literature, making this a highly useful reference
  • Expanded coverage of diagnostics, and more discussion of methods of model fitting, model selection and prediction
  • More than 200 problems throughout the book plus outline solutions

Concise, mathematically clear, and comprehensive, Linear Regression Analysis, Second Edition, serves as both a reliable reference for the practitioner and a valuable textbook for the student.

From the Inside Flap

An extensive treatment of a key method in the statistician’s toolbox

For more than two decades, the First Edition of Linear Regression Analysis has been an authoritative resource for one of the most common methods of handling statistical data. There have been many advances in the field over the last twenty years, including the development of more efficient and accurate regression computer programs, new ways of fitting regressions, and new methods of model selection and prediction. Linear Regression Analysis, Second Edition, revises and expands this standard text, providing extensive coverage of state-of-the-art theory and applications of linear regression analysis.

Requiring no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models, this new edition features:

  • Up-to-date accounts of computational methods and algorithms currently in use without getting entrenched in minor computing details
  • A careful and detailed survey of the research literature, making this a highly useful reference
  • Expanded coverage of diagnostics, and more discussion of methods of model fitting, model selection and prediction
  • More than 200 problems throughout the book plus outline solutions

Concise, mathematically clear, and comprehensive, Linear Regression Analysis, Second Edition, serves as both a reliable reference for the practitioner and a valuable textbook for the student.

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

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9780471019671: Linear Regression Analysis (Wiley Series in Probability and Statistics)

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