= Solution
{c}
For the <random vector> $\boldsymbol\epsilon=(\epsilon_1,\ldots,\epsilon_n)^\top$, its <covariance matrix> is
$$
\boxed{\Sigma=\mathbb E[(\boldsymbol\epsilon-\mathbb E\boldsymbol\epsilon)
(\boldsymbol\epsilon-\mathbb E\boldsymbol\epsilon)^\top],\qquad
\Sigma_{ij}=\operatorname{Cov}(\epsilon_i,\epsilon_j).}
$$
Its diagonal entries are <variances>, and its off-diagonal entries measure pairwise <covariance>. Finite <second moments> make every entry well defined.
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