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Multivariate Data and Multivariate Analysis

  • Brian Sidney Everitt
Chapter
  • 6.5k Downloads
Part of the Springer Texts in Statistics book series (STS)

Abstract

Multivariate data arise when researchers measure several variables on each “unit“ in their sample. The majority of data sets collected by researchers in all disciplines are multivariate. Although in some cases it may make sense to isolate each variable and study it separately, in the main it does not. In most instances the variables are related in such a way that when analyzed in isolation they may often fail to reveal the full structure of the data. With the great majority of multivariate data sets, all the variables need to be examined simultaneously in order to uncover the patterns and key features in the data. Hence the need for the collection of multivariate analysis techniques with which this book is concerned.

Keywords

Multiple Imputation Multivariate Data Probability Plot Multivariate Normal Distribution Sample Covariance Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2005

Authors and Affiliations

  • Brian Sidney Everitt
    • 1
  1. 1.King’s CollegeLondonUK

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