Discriminant functions are:
A) Linear combinations of the original (predictor) variables that maximize the between-to-within association, as measured by the sum-of-squares and cross-products (SSCP) matrices.
B) Uncorrelated linear combinations of the original (predictor) variables that maximize the between-to-within association, as measured by the sum-of-squares and cross-products (SSCP) matrices.
C) Correlated linear combinations of the original (predictor) variables that maximize the between-to-within association, as measured by the sum-of-squares and cross-products (SSCP) matrices.
D) Uncorrelated linear combinations of the original dependent variables that maximize the between-to-within association, as measured by the sum-of-squares and cross-products (SSCP) matrices.

Question

Quizplus · Accepted Answer

Discriminant functions are indeed uncorrelated linear combinations of the original (predictor) variables that aim to maximize the between-to-within group variance, as quantified by the sum-of-squares and cross-products (SSCP) matrices. This ensures that the groups are as distinct as possible on these functions.

Discriminant Functions Are