Discriminant Function Analysis

Objective

To classify people or objects into pre-defined groups.

Examples/Applications

• "Good" vs. "bad" markets
• "Good" vs. "bad" performers (brands, people)
• Concept acceptors vs. rejecters
• Users vs. non-users (brand, or product category)
• Users vs. prospects
• Responders to an offer vs. non-responders

Assumptions

• Equal covariance matrices for the groups being discriminated, others are the same as for regression analysis

Mechanics

• Means and standard deviations
• Within group matrices
• F ratios
• Discriminant functions
• Classification matrix
• Probabilities of group membership (hit-miss matrix)
• Eigenvalues

Seminal Articles/Texts

• Journal of Marketing Research, p.156, May 1969

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