Raymond Cattell’s use of factor analysis underlines its primary usefulness, that is, to take a large number of observable instances to measure an unobservable construct or constructs. Factor analysis is most frequently used to identify a small number of factors that may be used to represent relationships among sets of interrelated variables. Calculating a correlation matrix of all variables of interest is the starting point for factor analysis. The purpose of the factor-extraction phase is to extract the factors. The factors extracted by Statistical Package for the Social Sciences are almost never all of interest to the researcher. The common-sense criterion for retaining factors is that each retained factor must have some sort of face validity or theoretical validity; but prior to the rotation process, it is often impossible to interpret what each factor means. For display, the Rotated solution is selected by default and represents the essence of what factor analysis is designed to do.