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Regression Analysis,

Edition 2

Editors: By Rudolf J. Freund, William J. Wilson and Ping Sa

Publication Date: 27 Mar 2006

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Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.

Key Features

Examples and exercises contain real data and graphical illustration for ease of interpretation
Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statisticalsoftware package will work equally well

About the author

By Rudolf J. Freund, Texas A&M University, USA; William J. Wilson, University of North Florida, Jacksonville, FL, USA and Ping Sa, University of North Florida

Title Reviews

"...is well-written , well-organized, and succeeds in making regression analysis understandable, without being overly technical."—Donice McCune, Stephen F. Austin University

"I would say that this book is excellent from both a pedagogical perspective and a learning perspective (by the student). The instructor will enjoy discussing various concepts and then illustrating the concepts through the thorough examples. 6. This textbook will help give the students additional mathematical maturity for handling other statistics courses, especially applied courses like Analysis of Variance."—Steven Garren, James Madison University

ISBN: 9780120885978

Page Count: 480

Retail Price (USD) :

R. Lyman Ott, An Introduction to Statistical Methods,
and Data Analysis, 4th ed., 1993, 1050
Kleinbaum, Kupper, et.al., Applied Regression Analysis and Other Multivariate Methods, 3rd ed., 1998, 700
Neter, et.al., Applied Linear Statistical Models,
4th ed., 1996, 1400

Because of the universal appeal of statistics and statistical methodology, most graduate programs include as part of their curriculum one or two course in statistical methods. In addition, undergraduate students majoring in mathematics or statistics are required or encouraged to take courses in statistical methods. This book is intended to serve as a text for such courses. The book requires no mathematics beyond algebra, however, mathematically oriented students will still find the material in the text challenging