This is from measure theoretic probability class.
Let $Z$ have the Gaussian distribution with mean $0$ and variance $b$. Show that, then, $X=Z^2$ has the gamma distribution with shape index $a=1/2$ and scale parameter $c=1/2b$.
The instructor indicated using the following theorem:
Theorem--------------------------------------------------------------
Let $X$ be a random variable taking values in $(E,\mathscr{E})$. If $\mu$ is the distribution of $X$, that is, $\mu =\mathbb{P}\circ X^{-1}$, then,
$\mathbb{E}f\circ X=\mu f$
for every positive $\mathscr{E}$-measurable function $f$.
Concersely, if this holds for some measure $\mu$ and all positive $\mathscr{E}$-measurable functions, then $\mu$ is the distribution of $X$.
I guess this problem can be solved by computing $\mathbb{E}f\circ Z $, where $f(x)=x^2$,and applying the theorem to say $\mathbb{E}f\circ Z=\mu f$ and then identify $\mu$. But I really can't see how exactly, or is this a completely wrong direction?