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Titel: An R and S-Plus (R) Companion to Multivariate Analysis
Auteur: Brian S. Everitt
ISBN: 9781852338824
Conditie: Beetje gebruikt

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.

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. A website with all the datasets and code used in the book can be found at http://biostatistics.iop.kcl.ac.uk/publications/everitt/. 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. Brian Everitt is Emeritus Professor of Statistics, King’s College, London.

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

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