The
objective of discriminant analysis is to classify persons
or objects into two or more categories, using a set
of intervally scaled predictor variables.

Multiple
regression allows us to use an intervally scaled criterion
variable such as sales, market share, relative price,
or attitude. Often the criterion variable that we are
interested in is nominal, that is, purchaser - nonpurchaser,
heavy user - light user - nonuser, foreign - domestic
car purchaser, credit card - cash purchase, and so forth.
Regression analysis is inappropriate in such situations.
Instead, discriminant analysis should be used.

The
objective is to develop a model that will result in
a large proportion of the cases being correctly classified.
The discriminant equation can then be used to predict
to which class a new case will belong, or, more importantly,
to demonstrate which variables are most important in
distinguishing between the classes.