'''Discriminant function analysis''' is a statistical analysis to predict a [[categorical variable|categorical]] [[dependent variable|dependent]] [[Variable (mathematics)#Applied statistics|variable]] by one or more [[continuous variable|continuous]] or [[binary]] [[independent variable|independent]] variables. It is statistically the opposite of an [[ANOVA]] or [[MANOVA]], which is used to predict one (ANOVA) or multiple (MANOVA) continuous dependent variables by one or more independent categorical variables. It is useful in determining whether a set of variables is effective in predicting category membership.
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It is also a useful follow-up procedure to a MANOVA instead of doing a series of one-way ANOVAs, for ascertaining how the groups differ on the composite of dependent variables.
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In simple terms, discriminant function analysis is classification - the act of distributing things into classes or categories of the same type.
* [http://www2.chass.ncsu.edu/garson/pa765/discrim.htm Course notes, Discriminant function analysis by G. David Garson, NC State University]
* [http://www.psychstat.missouristate.edu/multibook/mlt03m.html Course notes, Discriminant function analysis by David W. Stockburger, Missouri State University]
