This quantity is minimized for an unbiased estimator that is a function of a complete and sufficient statistic by the Lehmann–Scheffé (“LAY-man shef-FAY”) theorem. Ronald Fisher developed a test that generalizes the t-test to more than two groups named for the “analysis of” this quantity. (10[3]-5[1])For two random variables X and Y, the expected value of X times Y minus the product of the expected (10[2])values of X and Y gives this quantity’s “co-” (-5[1])form. (10[1])This quantity is the second (10[1])central moment (10[1])of a distribution, and is equal to the mean for a Poisson (“pwa-SAWN”) distribution. For a random variable X, this quantity is the [read slowly] expected value of X squared, minus the square of the expected value of X. For 10 points, the square of the standard deviation is equal (10[1])to (10[2])what measure of (10[1])spread? ■END■