In much research in social psychology it is impractical to get quantitative measure of the degree of effectiveness of certain social behaviors, yet associates can sense that effectiveness sufficiently well to detect those who manifest the behavior in very high or in very low degree. This paper develops a technique of biserial correlation from wide-spread classes to deal statistically with such situations, develops standard error formulas for it, and points to a wide range of usefulness for this type of technique.

In this paper it is demonstrated that the analysis of variance techniques yield results equivalent to the calculation of t by means of expressions based on the short or the long formula. It is also shown that the covariance technique gives results equivalent to those obtained by means of the formula for t which should be used with matched groups. The conditions necessary for equivalent results are such that the conventional formulas for t would normally be used rather than the variance or covariance techniques. However, a knowledge of the relationships described in this paper should contribute to one's understanding of the variance and covariance techniques.

Adaptations of the micro-film projection method to the administration of both individual and group psychological tests are described, together with newly designed auxiliary equipment. The author cites examples of the application of this technique, which can be adapted to a variety of testing situations and which seems to be of unusual promise because of the attention value of visual projection.

It is shown that the L-method is basic to test-building and to all combining of scores where the several sub-parts of a composite are weighted according to their respective standard deviations, i.e., with “equal gross score weights” or by “adding the several sub-scores.” With chiefly a listing adding machine, a few celluloid strips, and a master matrix table of L's, one may, in a fraction of the time and with equally good or even better practical results, easily duplicate, with test-building material most of the feats obtainable by multiple regression equations.

Up to the present only empirical methods have been available for determining the number of factors to be extracted from a matrix of correlations. The problem has been confused by the implicit attitude that a matrix of intercorrelations between psychological variables has a rank which is determinable. A table of residuals always contains error variance and common factor variance. The extraction of successive factors increases the proportion of error variance remaining to common factor variance remaining, and a point is reached where the extraction of more dimensions would contain so much error variance that the common factor variance would be overshadowed. The critical value for this point is determined by probability theory and does not take into account the size of the residuals. Interpretation of the criterion is discussed.

A case studied in a previous paper, concerning the changes of the relative number of individuals of different types in a social group, is treated under more general assumptions. It is shown that under those more general conditions periodical fluctuations in the structure of the social group may occur.