Applied Linear Regression (Wiley Series in Probability and Statistics) - Hardcover

Weisberg, Sanford

Hardcover

ISBN 10: 0471663794 ISBN 13: 9780471663799

Verlag: John Wiley & Sons, 2005

Inhaltsangabe

Applied Linear Regression, Third Edition is thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, this Third Edition stresses using graphical methods to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. This text is an excellent tool for learning how to use linear regression analysis techniques to solve and gain insight into real-life problems.

Über diesen Titel

Über die Autorin bzw. den Autor

SANFORD WEISBERG, PhD, is Professor of Statistics and Director of the Statistical Consulting Service at the University of Minnesota. He has authored or coauthored three popular texts for John Wiley & Sons, Inc. and is a Fellow of the American Statistical Association.

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Master linear regression techniques with a new edition of a classic text
 
Reviews of the Second Edition:
 
"I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression."
--Technometrics, February 1987
 
"Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis."
--American Scientist, May-June 1987
 
Applied Linear Regression, Third Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Third Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results.
 
The Third Edition incorporates new material reflecting the latest advances, including:
* Use of smoothers to summarize a scatterplot
* Box-Cox and graphical methods for selecting transformations
* Use of the delta method for inference about complex combinations of parameters
* Computationally intensive methods and simulation, including the bootstrap method
* Expanded chapters on nonlinear and logistic regression
* Completely revised chapters on multiple regression, diagnostics, and generalizations of regression
 
Readers will also find helpful pedagogical tools and learning aids, including:
* More than 100 exercises, most based on interesting real-world data
* Web primers demonstrating how to use standard statistical packages, including R, S-Plus(r), SPSS(r), SAS(r), and JMP(r), to work all the examples and exercises in the text
* A free online library for R and S-Plus that makes the methods discussed in the book easy to use
 
With its focus on graphical methods and analysis, coupled with many practical examples and exercises, this is an excellent textbook for upper-level undergraduates and graduate students, who will quickly learn how to use linear regression analysis techniques to solve and gain insight into real-life problems.

Details zur Ausgabe

• Verlag: John Wiley & Sons
• Erscheinungsdatum: 2005
• Sprache: Englisch
• ISBN 10: 0471663794
• ISBN 13: 9780471663799
• Einband: Gebundene Ausgabe
• Auflage: 3
• Anzahl der Seiten: 336
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Nicht verfügbar