Applied Regression Analysis
A Research Tool
J.O. Rawlings(Author)
Brooks/Cole (Publisher)
Published on 31. January 1998
Book
Hardback
576 pages
978-0-534-09246-7 (ISBN)
Article exhausted; check for reprint
Description
Providing an introduction to modern regression analysis, this text emphasises understanding concepts rather than computational details or mathematical proofs. The frequent discussions of computing with SAS allows emphasis on whole concepts rather than conceptual details. This text includes topics unique for a book at this level, such as a chapter on a geometric interpretation of least square analysis, coverage of reparametrization, regression diagnostics including Gabriel's biplots and the analysis of unbalanced data. The text uses matrix notation throughout and includes extensive discussions on the application of regression models to analysis of variance problems, the limitations of stepwise regression procedures and of analyzing highly colinear data. This book should be of interest to degree and diploma students taking courses in statistics.
More details
Series
Language
English
Place of publication
CA
United States
Publishing group
Cengage Learning, Inc
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 230 mm
Weight
1140 gr
ISBN-13
978-0-534-09246-7 (9780534092467)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Book
04/2001
2nd Edition
Springer
€128.39
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Content
Review of simple regression. Introduction to matrices. Multiple regression in matrix notation. Analysis of variance and quadratic forms. Case study: five independent variables. Geometric interpretation of least squares. Model development: selection of variables. Class variables in regression. Problem areas in least squares. Regression diagnostics. Transformations of variables. Colinearity. Case study: colinearity problems. Response curve modeling. Case study: response surface modeling. Analysis of unbalanced data. Case study: analysis of unbalanced data. Appendix. Tables. Answers to selected exercises. Bibliography. Index.