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

- Canonical correlation analysis 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.