336 THE FACTORS OF THE MIND how they are related to each other and to the more import- ant alternatives that have been proposed. Let us begin with the tetrad-difference criterion. If we regard the correlation table as a matrix or determinant arising from the solution of a set of linear equations,1 this criterion can be reduced to a very simple form. As has often been pointed out, it is—under a different title—the regular method for demon- strating that a determinant is of unit rank.2 The great objection to its use is the time and labour involved : with a dozen tests the intercorrelations would yield 1,485 tetrad differences to calculate (not, however, all independent) ; with Thurstone's latest table [122] over a million. But when the determinant is symmetrical, it is in theory unnecessary to compute all the tetrad differences : it is sufficient 3 to show that the principal tetrad differences—i.e. the diagonal minors of order 2—are all zero. The sum of these diagonal minors, EE Tn ^ = (Er^ — EEr^f. If, therefore, the correlation matrix is of unit rank, the sum of the squares of all the correlations (inter- and self-) must be equal to the square of the sum of the self-correlations, i.e. squares of the saturations with the single factor : in other words, the standard deviation 4 of the correlations should be equal to — X the total hypothetical test-variance. This hypothetical total can be determined with sufficient accuracy by the methods described in the appendix ; and the probable error of the standard deviation can be estimated in the usual way. It is curious to note that this form of the tetrad-difference criterion de- pends on calculating precisely those tetrad differences which the ordinary form of the criterion omits. Since Era = Evt = Evf (where vt and Vf denote the n test- 1 Cf. Marks of Examiners, p. 247. 2 The * tetrad ' is a two-rowed minor determinant renamed ; and the ' tetrad difference ' its expansion. Hence the criterion may be regarded as a special application of the familiar property of determinants, namely, that * if the corresponding elements of two columns (or rows) are proportional, the determinant vanishes/ For the criterion as a theorem in matrix algebra, see Cullis [26], 1918, II, pp. 93, 139; and cf. Bocher [15], 1907, p. 34 f. 3 Strictly we ought also to show that the diagonal minors of order 3 are also zero. But this is needed only to rule out certain patterns involving negative signs which are never likely to arise in psychological work. 4 The c unadjusted' standard deviation, if we are dealing, not with a bipolar matrix of residuals, but with an observed table of positive correlations.