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Revision as of 10:57, 29 June 2001

Multivariate Statistical Analysis is the name used to describe a collection of procedures which involve observation and analysis of more than one statistical variable at a time.


There are many different models, each with its own type of analysis:

  1. Correlation analysis simply tries to establish whether or not there are linear relationships among the variables.
  1. Regession analysis attempts to determine a linear formula that can describe how some variables respond to changes in others .
  1. Principal component analysis attempts to determine a smaller set of synthetic variables that could explain the original set.
  1. Discriminant Function or Canonical Variate Analyses attempt to establish whether a set of variables can be used to distinguish between two or more groups.