Here's an identity related to the variance that people might find useful:
$$
\begin{align}
Var(X) &= E[(X - E[X])^{2}] \\
&= E[X^{2} - 2XE[X] + (E[X])^{2}] \\
&= E[X^{2} - 2E[X]E[X] + (E[X])^{2} \\
&= E[X^{2}] - (E[X])^{2}
\end{align}
$$
where the third step is from the linearity of expectations.

Here's an identity related to the variance that people might find useful: $$ \begin{align} Var(X) &= E[(X - E[X])^{2}] \\ &= E[X^{2} - 2XE[X] + (E[X])^{2}] \\ &= E[X^{2} - 2E[X]E[X] + (E[X])^{2} \\ &= E[X^{2}] - (E[X])^{2} \end{align} $$ where the third step is from the linearity of expectations.