Questionable Multivariate Statistical Inference in Wildlife Habitat and Community Studies

Abstract

We analyzed a data set constructed from functionally unrelated, easily collected observations (e.g., meat, stock, and liquor prices) around Fort Collins, Colorado, using principal components analysis (PCA), canonical correlation analysis (CC), and discriminant function analysis (DFA). Each produced seemingly significant results and suggested strong relationships between the variables measured. We suggest that multivariate techniques can provide invalid inferences when used with data containing no relationships. We question the use of these techniques in studies of wildlife habitat.