 By Jensen's inequality, a convex function as transformation will introduce positive bias, while a concave function will introduce negative bias, and a function of mixed convexity may introduce bias in either direction, depending on the specific function and distribution.That is, for a non-linear function "f" and a mean-unbiased estimator "U" of a parameter "p", the composite estimator "f"("U") need not be a mean-unbiased estimator of "f"("p").For example, the square root of the unbiased estimator of the population variance is "not" a mean-unbiased estimator of the population standard deviation