
Methods and Applications of Linear Models
Regression and the Analysis of Variance
Ronald R. Hocking(Author)
Wiley (Publisher)
2nd Edition
Published on 7. April 2003
Book
Hardback
776 pages
978-0-471-23222-3 (ISBN)
Article exhausted; check for reprint
Description
The Second Edition has been rearranged and reorganized, as well as fully updated and expanded to cover new developments.
* Includes material on the AVE method and explains existing information in an even more user-friendly form.
* Includes additional exercises.
* Describes a general approach to the analysis of unbalanced mixed models
* Uses data-based approach to development and analysis.
* Data sets will be available on an FTP site
Reviews / Votes
"...presents a thorough treatment of the concepts and methods of linear model analysis and illustrates them with numerical and conceptual examples..." (Quarterly of Applied Mathematics, Vol. LXII, No. 1, March 2004) "...an essential desktop reference book...it should definitely be on your bookshelf." (Technometrics, Vol. 45, No. 4, November 2003)More details
Series
Edition
2., Auflage
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
Professional and scholarly
Edition type
Revised edition
Illustrations
Illustrations
Dimensions
Height: 24.4 cm
Width: 16.2 cm
Thickness: 40 mm
Weight
1162 gr
ISBN-13
978-0-471-23222-3 (9780471232223)
Schweitzer Classification
Other editions
New editions

Book
09/2013
3rd Edition
Wiley
€155.00
Shipment within 15-20 days
Previous edition
Book
06/1996
Wiley
€87.28
Article exhausted; check for reprint
Person
RONALD R. HOCKING, PhD, is Professor Emeritus in the Department of Statistics at Texas A&M University. He is also co-owner of PenHock Statistical Consultants in Ishpeming, Michigan.
Content
Preface to the Second Edition.
Preface to the First Edition.
PART I: REGRESSION MODELS.
Introduction to Linear Models.
Regression on Functions of One Variable.
Transforming the Data.
Regression of Functions of Several Variables.
Collinearity in Multiple Linear Regression.
Influential Observations in Multiple Linear Regression.
Polynomial Models and Qualitative Predictors.
Additional Topics.
PART II: ANALYSIS OF VARIANCE MODELS.
Introduction to Analysis of Variance Models.
Fixed Effects Models I: One-Way Classification of Means.
Fixed Effects Models II: Two-Way Classification of Means.
Fixed Effects Models III: Multiple Crossed and Nested Factors.
Mixed Models I: The AOV Method with Balanced Data.
Mixed Models II: The AVE Method with Balanced Data.
Mixed Models III: Unbalanced Data.
PART III: MATHEMATICAL THEORY OF LINEAR MODELS.
Distribution of Linear and Quadratic Forms.
Estimation and Inference for Linear Models.
Simultaneous Inference: Tests and Confidence Intervals.
Appendix A. Mathematics.
Appendix B. Statistics.
Appendix C. Statistical Tables.
Appendix D. Data Tables.
References.
Index.