If _j, an unbiased estimator of _j, is also a consistent estimator of _j, then when the sample size tends to infinity: A)the distribution of _j collapses to a single value of zero. B)the distribution of _j diverges away from a single value of zero. C)the distribution of _j collapses to the single point _j. D)the distribution of _j diverges away from _j.

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If an estimator is both unbiased and consistent, then it is also asymptotically normal. As the sample size tends to infinity, the distribution of the estimator collapses to a single point that is the true value of the parameter being estimated. Therefore, the distribution of 11eb6b8a_02c1_b45a_bf83_6f67124f4ab2_TB8272_11 _j collapses to the single point 11eb6b8a_02c1_b45b_bf83_cf5beb0ba1e3_TB8272_11 _j.

If j, an Unbiased Estimator of j, Is

If _j, an Unbiased Estimator of _j, Is