Discriminant Analysis (DA), also known as Discriminant Function Analysis, is a statistical technique used for classification and prediction of group membership. It is particularly useful when the dependent variable is categorical, and the independent variables are continuous. The goal of Discriminant Analysis is to find the best combination of independent variables that can distinguish between two or more groups or categories.

Discriminant Analysis relies on several assumptions to produce reliable results. These assumptions are important to consider when applying the technique to a dataset.