Fordisc population affinity analysis uses what approach?

Fordisc population affinity analysis uses what approach?

• A. Classify an individual to the group it most closely resembles, iteratively eliminating the weakest matches until 2-4 groups remain
• B. Determine a single best-match to a population
• C. Use genetic data to estimate ancestry
• D. Date the skeleton

Answer: (A)

Fordisc uses a multivariate classification approach that compares an individual’s measurements to a database of reference populations and then narrows the field by discarding the weakest matches until only a small number of closest groups remain. In practice, this means the software evaluates similarity across many populations and presents a short list of likely populations (often 2–4), rather than declaring a single best-match. This reflects inherent overlap among populations and the uncertainty in morphometric data. It does not rely on genetic data and it does not date the skeleton.

Fordisc uses a multivariate classification approach that compares an individual’s measurements to a database of reference populations and then narrows the field by discarding the weakest matches until only a small number of closest groups remain. In practice, this means the software evaluates similarity across many populations and presents a short list of likely populations (often 2–4), rather than declaring a single best-match. This reflects inherent overlap among populations and the uncertainty in morphometric data. It does not rely on genetic data and it does not date the skeleton.