 Conversely, MSE can be minimized by dividing by a different number (depending on distribution), but this results in a biased estimator.This number is always larger than "n" − 1, so this is known as a shrinkage estimator, as it "shrinks" the unbiased estimator towards zero; for the normal distribution the optimal value is "n" + 1.Suppose "X"1, ..., "X""n" are independent and identically distributed (i.i.d.)