2.Let X_1…X_n be i.i.d random variables with pdf f_θ(x)= θx^(θ-1)1(0<x<1) where θ is some positive number

Question

a) is the parameter θ identificable
Y
N
b)
Compute the maximum likelihood estimator Ӫ of θ.
(Enter Sigma_i(g(X_i)) for the sum ∑ni=1g(Xi), e.g. enter Sigma_i(X_i^2) for ∑ni=1X2i, enter Sigma_i(ln(X_i)) for ∑ni=1ln(Xi). Do not forget any necessary n in your answer, e.g. ˉXn will need to be entered as Sigma_i(X_i)/n . Do not worry about the parser not rendering correctly, as the grader will still work independently. If you would like proper rendering, enclose Σi(g(Xi)) in parentheses i.e. use (Σi(g(Xi))).)
Maximum likelihood estimator Ӫ