Covariance

  The covariance between two random variables X₁,X_j is the following moment about the means E(X_i), E(X_j) ( Expectation Value)

It vanishes for independent variables. The converse is not true: a covariance of zero is not a sufficient condition for independence. The are the variances of the variables. The C_ij constitute the covariance matrix . The covariance matrix is always symmetric and positive semi-definite. It is diagonal if all n variables are independent. Its determinant is zero if linear relations exist between variables.