Variance of continuous probability distribution

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Show that for a random variable $X \sim f(x):=(2\pi)^{-\frac{1}{2}}exp(\frac{-x^2}{2})$:

$1)\ \ E[X] = 0$

$2)\ \ Var(X) = 1$

I already proved $1)$ without any difficulties, because $$E[X]=(2\pi)^{-\frac{1}{2}}\int_\mathbb R x e^{\frac{-x^2}{2}}$$ is easy to calculate. However, I got stuck with $2)$, because I don't know how to calculate $$E[X^2]=(2\pi)^{-\frac{1}{2}}\int_\mathbb R x^2 e^{\frac{-x^2}{2}}$$

Any help is greatly appreciated!

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Do the following,

$-\frac{\partial}{\partial a} exp(-ax^2) = x^2exp(-ax^2)$

Integrate both sides,

$-\frac{\partial}{\partial a}\int exp(-ax^2) dx = \int x^2exp(-ax^2) dx$

$-\frac{\partial}{\partial a}\sqrt{\frac{\pi}{a}} = \int x^2exp(-ax^2) dx $

Take the derivative, set a = 1/2.