Question

What statistical assumptions must be met for the use of discriminant analysis?   

Answer 1

Assumptions of discriminant analysis:

• It is assumed that the data (for the variables) represent a sample from a multivariate normal distribution.
• It is assumed that the variance/covariance matrices of variables are homogeneous across groups and it makes the assumption that the group covariance matrices are equal.
• It assumes linear relations among the independent variables.
• Another assumption of discriminant function analysis is that the variables that are used to discriminate between groups are not completely redundant. As part of the computations involved in discriminant analysis, you will invert the variance/covariance matrix of the variables in the model. If any one of the variables is completely redundant with the other variables then the matrix is said to be ill-conditioned, and it cannot be inverted. For example, if a variable is the sum of three other variables that are also in the model, then the matrix is ill-conditioned.