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Point out the correct statement.(a) Asymptotics are incredibly useful for simple statistical inference and approximations(b) Asymptotics often lead to nice understanding of procedures(c) An estimator is consistent if it converges to what you want to estimate(d) All of the mentionedThe question was posed to me during an internship interview.The above asked question is from Likelihood in division Statistical Inference and Regression Models of Data Science

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Right answer is (d) All of the mentioned

To explain I would say: Consistency is NEITHER NECESSARY nor SUFFICIENT for ONE estimator to be better than another.



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