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:
- 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 component analysis attempts to determine a smaller set of synthetic variables that could explain the original set.
- Discriminant Function or Canonical Variate Analyses attempt to establish whether a set of variables can be used to distinguish between two or more groups.