The estimate of the variance covariance matrix of a p-vector obtained with an nxp data matrix is important when doing principal components because Select one: 0 a. The eigenvalues of the estimate of the variance covariance matrix are the variances of the principal components 0 b. The eigenvectors of the estimate of the variance covariance matrix are the principal components 0 c. The variance covariance matrix contains the vectors that are the principal components 0 d. The sum of the diagonal elements of the variance covariance matrix is the same as the dimension of the principal components no matter what the diagonal elements are