The use of factor analysis with behavioral data is examined critically. Although there are good reasons to make wider use of factor analytic techniques in behavioral research, several important pitfalls should be avoided. Samples should be of adequate size, both absolutely and relative to the number of variables analysed. Variables should be reliable and devoid of scoring dependencies. One should not allow the same components to appear in different ratio variables, difference scores and composites. Variables and subjects should be carefully selected to represent a substantive design for the study. Ideally this design should stem from empirically-based, well reasoned theory. Careful thought should be given to the question of the number of factors to extract. Rotation of factors should be based on the model reflected in the design for the study. One should be wary of using mathematical-statistical indices with factor coefficients. The correlation, as such, and the standard error for a correlation, do not have the same properties when applied to arrays of factor coefficients as when used with free-to-vary numbers.