Discriminant function analysis is a statistical analysis to predict a categorical dependent variable by one or more continuous or binary 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.
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.
See also
Wikiversity has learning resources about Discriminant function analysis
External links
- Course notes, Discriminant function analysis by G. David Garson, NC State University
- Course notes, Discriminant function analysis by David W. Stockburger, Missouri State University
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