Jelaskan Sababaraha harti prasarat dari Téoréma Rao-Blackwell dalam bahasa sunda

Hiji estimator nyaéta hiji variabel acak nu bisa diobservasi (upamana dina statistik) dipaké keur ngira-ngira kuantita nu teu ka-observasi. For example, one may be unable to observe the average height of all male students at the University of X, but one may observe the heights of a random sample of 40 of them.  The average height of those 40—the "sample average"—may be used as an éstimator of the unobservable "population average".

A sufficient statistic T(X) is an observable random variable such that the conditional probability distribution of all observable data X given T(X) does not depend on any of the unobservable quantities such as the méan or standard deviation of the whole population from which the data X was taken. In the most frequently cited examples, the "unobservable" quantities are paraméters that parametrize a known family of probability distributions according to which the data are distributed.

A Rao-Blackwell éstimator δ1(X) of an unobservable quantity θ is the conditional expectation E(δ(X) | T(X)) of some éstimator δ(X) given a sufficient statistic T(X).  Call δ(X) the "original estimator" and δ1(X) the "improved estimator".  It is important that the improved éstimator be observable, i.e., that it not depend on θ.  Generally, the conditional expected value of one function of these data given another function of these data does depend on θ, but the very definition of sufficiency given above entails that this one does not.

The mean squared error of an éstimator is the expected value of the square of its deviation from the unobservable quantity being estimated.