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An R and S-Plusi Companion to Multivariate Analysis (PDF eBook) 1st ed. 2005. Corr. 2nd printing 2007


An R and S-Plusi Companion to Multivariate Analysis (PDF eBook) 1st ed. 2005. Corr. 2nd printing 2007

eBook by Everitt, Brian S.

An R and S-Plusi Companion to Multivariate Analysis (PDF eBook)

£54.99

ISBN:
9781846281242
Publication Date:
30 Mar 2006
Edition:
1st ed. 2005. Corr. 2nd printing 2007
Publisher:
Springer Nature
Imprint:
Springer
Pages:
221 pages
Format:
eBook
For delivery:
Download available
An R and S-Plusi Companion to Multivariate Analysis (PDF eBook)

Description

Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results. This requires the use of one or other of the many methods of multivariate analysis, and the use of a suitable software package such as S-PLUS or R.In this book the core multivariate methodology is covered along with some basic theory for each method described. The necessary R and S-PLUS code is given for each analysis in the book, with any differences between the two highlighted. Graduate students, and advanced undergraduates on applied statistics courses, especially those in the social sciences, will find this book invaluable in their work, and it will also be useful to researchers outside of statistics who need to deal with the complexities of multivariate data in their work. From the reviews:This text is much more than just an R/S programming guide. Brian Everitt's expertise in multivariate data analysis shines through brilliantly. Journal of the American Statistical Association, June 2006

Contents

Multivariate Data and Multivariate Analysis.- Looking at Multivariate Data.- Principal Components Analysis.- Exploratory Factor Analysis.- Multidimensional Scaling and Correspondence Analysis.- Cluster Analysis.- Grouped Multivariate Data: Multivariate Analysis of Variance and Discriminant Function Analysis.- Multiple Regression and Canonical Correlation.- Analysis of Repeated Measures Data.

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