Principal Components as a Small Number of Interpretable Variables: Some Examples

  • I. T. Jolliffe
Part of the Springer Series in Statistics book series (SSS)


The original purpose of PCA was to reduce a large number (p) of variables to a much small number (m) of PCs whilst retaining as much as possible of the variation in the p original variables. The technique is especially useful if m « p,and if the m PCs can be readily interpreted.


Component Number Crowded Condition Anatomical Measurement Stock Market Price Basic Amenity 
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Copyright information

© Springer Science+Business Media New York 1986

Authors and Affiliations

  • I. T. Jolliffe
    • 1
  1. 1.Mathematical InstituteUniversity of KentKentEngland

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