We have N measurements collected as i.i.d. observations from a random variable x and the pdf of measurements is in binomial form as N p(x[r] |s)=() s*[n] (1-s)(N-*[n]) for n = 0,..(N-1). 1.... where s...

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Extracted text: We have N measurements collected as i.i.d. observations from a random variable x and the pdf of measurements is in binomial form as N p(x[r] |s)=() s*[n] (1-s)(N-*[n]) for n = 0,..(N-1). 1.... where s denotes the probability of success. a. Write p(x | s) and design a ML (Maximum Likelihood) estimator for s. b. Show that the ML estimator is unbiased. (Hint: E[ x [n] ]= Ns for the binomial distribution) c. Calculate the CRLB (Cramer-Rao lower bound). d. Show that the estimator is efficient.