Synopses & Reviews
A popular statistical text now updated and better than ever!
The ready availability of high-speed computers and statistical software encourages the analysis of ever larger and more complex problems while at the same time increasing the likelihood of improper usage. That is why it is increasingly important to educate end users in the correct interpretation of the methodologies involved. Now in its second edition, Methods and Applications of Linear Models: Regression and the Analysis of Variance seeks to more effectively address the analysis of such models through several important changes. Notable in this new edition:
- Fully updated and expanded text reflects the most recent developments in the AVE method
- Rearranged and reorganized discussions of application and theory enhance texts effectiveness as a teaching tool
- More than 100 new exercises in the areas of regression and analysis of variance
As in the First Edition, the author presents a thorough treatment of the concepts and methods of linear model analysis, and illustrates them with various numerical and conceptual examples, using a data-based approach to development and analysis. Data sets, available on an FTP site, allow readers to apply analytical methods discussed in the book.
Review
“...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)
Synopsis
The popular First Edition of this book provided a thorough treatment of the concepts and methods of linear model analysis and illustrated them with numerical and conceptual examples. Revised to enhance its value as a teaching text, the Second Edition presents the material in a conceptually simple way so that users could more easily understand the applications of the methods and be able to use the appropriate computer applications to perform the analysis.
Synopsis
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.
* An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.
Synopsis
* An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley editorial department.
About the Author
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.
Table of Contents
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.