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An introduction to applied multivariate analysis with R / Brian Everitt, Torsten Hothorn

Main Author Everitt, Brian Coauthor Hothorn, Torsten Country Estados Unidos. Edition 1st ed Publication New York : Springer Science+Business Media, 2011 Description XIV, 273 p. : il. ; 24 cm Series Use R ISBN 978-1-441-99649-7 CDU 519.2
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Holdings
Item type Current location Call number Status Date due Barcode Item holds Course reserves
Monografia Biblioteca Geral da Universidade do Minho
BGUM 519.2 - E Checked out 2022-03-14 417265

Licenciatura em Estatística Aplicada Análise Multivariada e Aplicações 1º semestre

Mestrado em Estatística para Ciência de Dados Análise Estatística Multivariada 2º semestre

Total holds: 0

Enhanced descriptions from Syndetics:

The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.

An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

Author notes provided by Syndetics

Brian Everitt is Professor Emeritus at King's College, London. He is the author of over 50 books on statistics.

Torsten Hothorn is Professor of Biostatistics in the Faculty of Mathematics, Computer Science and Statistics at Ludwig-Maximilians-Universität München in Germany.

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