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. For two random variables X and Y, the expected (-5[1])value of X times Y minus the product of (10[1])the expected (10[1])values of X and Y (-5[1])gives this quantity’s (-5[1])“co-” form. (10[2])This (10[1])quantity (10[2])is the second central moment 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 to (10[1])what measure of (10[4]0[1])spread? ■END■