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An Introduction to Applied Multivariate Analysis with R (Use R)

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An Introduction to Applied Multivariate Analysis with R (Use R) Cover

 

Synopses & Reviews

Publisher Comments:

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.

About the Author

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.

Table of Contents

Multivariate data and multivariate analysis.- Looking at multivariate data: visualization.- Principal components analysis.- Multidimensional scaling.-

Product Details

ISBN:
9781441996497
Author:
Everitt, Brian
Publisher:
Springer
Author:
Hothorn, Torsten
Location:
New York, NY
Subject:
Statistics
Subject:
Multivariate analysis
Subject:
Statistical Theory and Methods
Subject:
Statistical Theory and Methods <p>Comprehensively covers a wide variety of multivariate analysis techniques using  R</p><p>Covers the use of Rs graphical capabilities for interpretation of multivariate data</p><p>Provides extensive examples of R code use
Subject:
Mathematics | Probability and Statistics
Subject:
Mathematics - General
Subject:
The Arts
Subject:
mathematics and statistics
Subject:
Mathematical statistics
Copyright:
Edition Description:
2011
Series:
Use R
Publication Date:
20110601
Binding:
TRADE PAPER
Language:
English
Pages:
288
Dimensions:
235 x 155 mm

Related Subjects

Reference » Science Reference » Technology
Science and Mathematics » Mathematics » General
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Science and Mathematics » Mathematics » Software

An Introduction to Applied Multivariate Analysis with R (Use R) New Trade Paper
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