Linear discriminant function analysis (i.e., discriminant analysis) performs a multivariate test of differences between groups. In addition, discriminant analysis is used to determine the …

Discriminant analysis works by creating one or more linear combinations of predictors, creating a new latent variable for each function. These functions are called discriminant functions.

Mar 26, 2024 · Discriminant analysis is a statistical method used to determine the likelihood that an observation belongs to a particular group based on predictor variables. Commonly used in …

Discriminant function analysis (DFA) is a statistical procedure that classifies unknown individuals and the probability of their classification into a certain group (such as sex or ancestry group).

This can be assessed by plotting the discriminant function scores for at least the first two functions and comparing them to see if they are about the same size and spread.

May 14, 2025 · This guide introduces discriminant function analysis in multivariate applications, covering computational steps and interpretation tips.

Discriminant analysis is a classification problem, where two or more groups or clusters or populations are known a priori and one or more new observations are classified into one of the …

Discriminant function analysis is the statistical analysis used to analyze data when the dependent variable or outcome is categorical and independent variable or predictor variable is parametric.

Discriminant function analysis is used to predict group membership based on a linear combination of interval predictor variables.

Discriminant analysis builds a predictive model for group membership. The model is composed of a discriminant function (or, for more than two groups, a set of discriminant functions) based on …