Multivariate Statistical Methods: A Primer / Edition 2

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Overview

Multivariate Statistical Methods: A Primer introduces multivariate methods to non-mathematicians and provides a general overview without overwhelming the novice with comprehensive details. This third edition is a thoroughly revised and updated version of a best-selling introductory textbook and primer. It retains the author's trademark clear, concise style and focuses on examples in the biological and environmental sciences. Topics new to this edition include confirmatory factor analysis, the use of mixture models for cluster analysis, and the emerging techniques of data mining and neural networks. While not linked to any specific software package, the book now includes an appendix comparing and contrasting various statistical software packages, such as Stata, Statistica, SAS, and Genstat. The author also notes which software was used for a particular example, when appropriate. In his efforts to produce a book that is as short as possible and that enables readers to begin to use multivariate methods in an intelligent manner, the author has produced a succinct and handy reference. With updated information on multivariate analyses, new examples using the latest software, and updated references, this book provides a timely introduction to useful tools for statistical analysis.
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Editorial Reviews

Booknews
An introduction for nonmathematicians who have previously taken a standard introductory course of statistical methods. The first five chapters deal with general aspects of multivariate data, such as tests of significance and measuring and testing multivariate distances. The rest of the book covers multivariate methods in terms of current use, including factor analysis, cluster analysis, and multidimensional scaling. This second edition contains new material on ordination, logistic regression, and ordination, plus exercises. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780412603006
  • Publisher: CRC Press
  • Publication date: 7/1/1994
  • Edition description: Older Edition
  • Edition number: 2
  • Pages: 232
  • Product dimensions: 5.56 (w) x 8.44 (h) x 0.50 (d)

Table of Contents

Ch. 1 The material of multivariate analysis 1
Ch. 2 Matrix algebra 17
Ch. 3 Displaying multivariate data 27
Ch. 4 Tests of significance with multivariate data 35
Ch. 5 Measuring and testing multivariate distances 59
Ch. 6 Principal components analysis 75
Ch. 7 Factor analysis 91
Ch. 8 Discriminant function analysis 105
Ch. 9 Cluster analysis 125
Ch. 10 Canonical correlation analysis 143
Ch. 11 Multidimensional scaling 163
Ch. 12 Ordination 177
Ch. 13 Epilogue 201
App Computer packages for multivariate analyses 205
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