Discriminant function analysis: Difference between revisions

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'''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 statisticallydifferent the opposite offrom an [[ANOVA]] or [[MANOVA]], which is used to predict one (ANOVA) or multiple (MANOVA) continuous dependent variables by one or more independent categorical variables instead. ItDiscriminant function analysis is useful in determining whether a set of variables is effective in predicting category membership.

ItMoreover, isit alsois 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.

In simple terms, discriminant function analysis is classification - the act of distributing things into classes or categories of the same type.