Introduction

Discriminant analysis is used to distinguish distinct sets of observations and allocate new observations to previously defined groups. For example, if a study was to be carried out in order to investigate the variables that discriminate between fruits eaten by (1) primates, (2) birds, or (3) squirrels, the researcher could collect data on numerous fruit characteristics of those species eaten by each of the animal groups. Most fruits will naturally fall into one of the three categories. Discriminant analysis could then be used to determine which variables are the best predictors of whether a fruit will be eaten by birds, primates, or squirrels. Discriminant analysis is commonly used in biological species classification, in medical classification of tumors, in facial recognition technologies, and in the credit card and insurance industries for determining risk. The main goals of discriminant analysis are discrimination and classification. The assumptions regarding discriminant...