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:
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.
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Regression and analysis of variance represent 90 of all applied statistical analysis. This book is unique in that it represents a unified treatment of these two areas. This view is carried out through chapters discussing linear models, distribution of linear and quadratic forms, estimation and inference for simple linear models, single predictor regression models, multiple predictor regression models as well as factorial models. A disk of data sets will be included in the book.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.
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Book Description Wiley-Interscience, 2003. Hardcover. Book Condition: New. Bookseller Inventory # P11047123222X