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An Introduction to Applied Multivariate Analysis with R (Paperback, 2011 ed.)
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An Introduction to Applied Multivariate Analysis with R (Paperback, 2011 ed.)
Series: Use R!
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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.
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