Methods of Multivariate Analysis / Wiley Series in Probability and Statistics Bd.1 (PDF)

Amstat News asked three review editors to rate their top
five favorite books in the September 2003 issue. Methods of
Multivariate Analysis was among those chosen.

When measuring several variables on a complex experimental unit,
it is often necessary to analyze the variables simultaneously,
rather than isolate them and consider them individually.
Multivariate analysis enables researchers to explore the joint
performance of such variables and to determine the effect of each
variable in the presence of the others. The Second Edition of Alvin
Rencher's Methods of Multivariate Analysis provides students
of all statistical backgrounds with both the fundamental and more
sophisticated skills necessary to master the discipline.

To illustrate multivariate applications, the author provides
examples and exercises based on fifty-nine real data sets from a
wide variety of scientific fields. Rencher takes a "methods"
approach to his subject, with an emphasis on how students and
practitioners can employ multivariate analysis in real-life
situations. The Second Edition contains revised and updated
chapters from the critically acclaimed First Edition as well as
brand-new chapters on:

* Cluster analysis

* Multidimensional scaling

* Correspondence analysis

* Biplots

Each chapter contains exercises, with corresponding answers and
hints in the appendix, providing students the opportunity to test
and extend their understanding of the subject. Methods of
Multivariate Analysis provides an authoritative reference for
statistics students as well as for practicing scientists and
clinicians.