Variance of Bernoulli Distribution/Proof 2

Proof 2
From the definition of Variance as Expectation of Square minus Square of Expectation:
 * $\operatorname{var} \left({X}\right) = E \left({X^2}\right) - \left({E \left({X}\right)}\right)^2$

From Expectation of Function of Discrete Random Variable:
 * $\displaystyle E \left({X^2}\right) = \sum_{x \mathop \in \operatorname{Im} \left({X}\right)} x^2 \Pr \left({X = x}\right)$

So:

Then: