For two random variates X and Y, the correlation is defined bY cor(X, Y) congruent (cov(X, Y))/(σ_X σ_Y), where σ_X denotes standard deviation and cov(X, Y) is the covariance of these two variables. For the general case of variables X_i and X_j, where i, j = 1, 2, ..., n, cor(X_i, X_j) = (cov(X_i, X_j))/sqrt(V_(i i) V_(j j)), where V_(i i) are elements of the covariance matrix. In general, a correlation gives the strength of the relationship between variables. For i = j, cor(X_i, X_i) = (cov(X_i, X_i))/σ_i^2 = 1.

covariance | covariance matrix | variance