Question

As on the previous page, let X1,... ,Xn be iid with pdf where θ > 0. (to) 2 Possible points (qualifiable, hidden results) Assume we do not actually get to observe Xı , . . . , X. . Instead let Yı , . . . , Y, be our observations where Yi = 1 (Xi 0.5) . Our goal is to estimate 0 based on this new data. What distribution does Y follow? First, choose the type of distribution: O Bernoulli O Poisson Norma O Exponential Second, enter the parameter of this distribution in terms of 0. Denote this parameter byme. (If the distribution is normal, enter only 1 parameter the mean). STANDARD NOTATION Submit You have made O of 3 attempts Save 1 possible point (qualifiable, hidden results) Write down a statistical model associated to this experiment. Is the parameter identifiable? And it is O Do not Submit You have made 1 of 3 attempts Save 2.0 Possible points (qualifiable, hidden results) Compute the Fisher information I (0). По answer this question correctly, your answer to part (a) needs to be correct.) 1 (θ)- STANDARD NOTATION Submit You have made O of 3 attempts Save 2.0 Possible points (qualifiable, hidden results) Compute the maximum likelihood estimator θ for θ in terms of Y Enter barY n forY) STANDARD NOTATION

Answer 1

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