For a random variable $X = (x_1,x_2,\ldots,x_n)^T$, I understand that the entries of the covariance matrix would just be the covariance of $x_i$ and $x_j$, but how do I find the eigenvalues and eigenvectors after that, and how does that turn into the eigendecomposition of the covariance matrix?