Eigenvalues

When extracting the canonical roots, STATISTICA will compute the eigenvalues. These can be interpreted as the proportion of variance accounted for by the correlation between the respective canonical variates. Note that the proportion here is computed relative to the variance of the canonical variates, that is, of the weighted sum scores of the two sets of variables; the eigenvalues do not tell how much variability is explained in either set of variables. STATISTICA will compute as many eigenvalues as there are canonical roots, that is, as many as the minimum number of variables in either of the two sets.