Sanford Weisberg 
Applied Linear Regression [EPUB ebook] 

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Praise for the Third Edition
‘…this is an excellent book which could easily be used as a
course text…’
–International Statistical Institute
The Fourth Edition of Applied Linear
Regression provides a thorough update of the basic theory
and methodology of linear regression modeling. Demonstrating the
practical applications of linear regression analysis techniques,
the Fourth Edition uses interesting, real-world
exercises and examples.
Stressing central concepts such as model building, understanding
parameters, assessing fit and reliability, and drawing conclusions,
the new edition illustrates how to develop estimation, confidence,
and testing procedures primarily through the use of least squares
regression. While maintaining the accessible appeal of each
previous edition, Applied Linear Regression, Fourth
Edition features:
* Graphical methods stressed in the initial exploratory phase,
analysis phase, and summarization phase of an analysis
* In-depth coverage of parameter estimates in both simple and
complex models, transformations, and regression diagnostics
* Newly added material on topics including testing, ANOVA, and
variance assumptions
* Updated methodology, such as bootstrapping, cross-validation
binomial and Poisson regression, and modern model selection
methods
Applied Linear Regression, Fourth Edition is an
excellent textbook for upper-undergraduate and graduate-level
students, as well as an appropriate reference guide for
practitioners and applied statisticians in engineering, business
administration, economics, and the social sciences.

€111.99
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关于作者

SANFORD WEISBERG, Ph D, is Professor of Statistics and Director of the Statistical Consulting Service in the School of Statistics at the University of Minnesota. He is also a coauthor of Applied Regression Including Computing and Graphics and An Introduction to Regression Graphics, both published by Wiley.

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语言 英语 ● 格式 EPUB ● 网页 368 ● ISBN 9781118594858 ● 文件大小 13.6 MB ● 出版者 John Wiley & Sons ● 发布时间 2013 ● 版 4 ● 下载 24 个月 ● 货币 EUR ● ID 2841374 ● 复制保护 Adobe DRM
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