Discriminant Analysis

Mary Earick Godby

where S i is the score for i th function, l in is the standardized coefficient for x n , n = 1, …, p . There is one CDF for each independent variable or one for the number of groups minus one, whichever number is the smaller of the two. For example, if there are three groups and five variables, two CDFs are generated. The first CDF explains the greatest percentage of variation between groups. Each successive CDF is independent of the previous function and explains less variance. The characteristic root or eigenvalue associated, with the CDF indicates the amount of variance explained by the function. The magnitude of the CDF coefficients indicates how important each variable is to group discrimination relative to the other variables. However, these coefficients may be misleading in the presence of correlation between the responses, that is, if there is a high degree of ...

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