Discriminant analysis is a statistical technique used in classification. In general, a classification problem features a categorical target variable with two or more known classes and one or more inputs to be used in the classification. Discriminant analysis assumes that the inputs are numeric (scale) variables, although practitioners often employ discriminant analysis when the inputs are a mixture of numeric and categorical variables. To use categorical variables as inputs in SPSS Statistics Discriminant, you must employ dummy variable coding. If your inputs are exclusively categorical, you might consider using logistic regression instead.
A classic example where discriminant analysis could be used is the oft-cited Fisher Iris data example. A botanist approached the great statistician and geneticist R. A Fisher with a classification problem. He had four...
