There are many different models, each with its own type of analysis:
Correlation analysis[?] simply tries to establish whether or not there are linear relationships among the variables.
Regression analysis attempts to determine a linear formula that can describe how some variables respond to changes in others .
Principal components analysis attempts to determine a smaller set of synthetic variables that could explain the original set.
Discriminant Function or Canonical variate analysis[?] attempt to establish whether a set of variables can be used to distinguish between two or more groups.
Principal coordinate analysis[?] attempts to determine a set of synthetic variables that best preserves the distance relationships between records.
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