Hi, I don't know how to solve this past exam question, and I can't find any course material that helps whatsoever

Suppose that a random variable X has the probability density function

$\displaystyle f_{X}(x)=\left\{\begin{array}{cc}\frac{e^{{-x/\theta}}}{\theta},& \mbox{} x>0; {} \theta >0;}\\0,& \mbox{} otherwise.\end{array}\right.$

Consider a random sample $\displaystyle X_{1}, X_{2},...,X_{n}$ from this distribution and let $\displaystyle T=k\sum{X_{i}^2}$

Find $\displaystyle k$ so that $\displaystyle T$ is an unbiased estimator of $\displaystyle \theta^2$

Thanks.

p.s. the sum is i=1 to n, i don't know how to latex that