Let X1, X2, . . . , Xn represent a random sample from a Rayleigh distribution with pdf
f(x; θ) = (x/θ) * eˣ²/⁽²θ⁾ for x > 0
(a) It can be shown that E(X₂ P ) = 2θ. Use this fact to construct an unbiased estimator of θ based on n i=1 X₂ i