Factor Analysis as a Classification Method - Factor Loadings

Let us now perform a principal components analysis and look at the two-factor solution. Specifically, let us look at the correlations between the variables and the two factors (or "new" variables), as they are extracted by default; these correlations are also called factor loadings.

STATISTICA

FACTOR

ANALYSIS

 Factor Loadings (Unrotated)

Principal components
Variable Factor 1 Factor 2
WORK_1 .654384 .564143
WORK_2 .715256 .541444
WORK_3 .741688 .508212
HOME_1 .634120 -.563123
HOME_2 .706267 -.572658
HOME_3 .707446 -.525602
Expl.Var 2.891313 1.791000
Prp.Totl .481885 .298500

Apparently, the first factor is generally more highly correlated with the variables than the second factor. This is to be expected because, as previously described, these factors are extracted successively and will account for less and less variance overall.