The null hypothesis of Levene’s test is that this quantity is equal across multiple groups. The Gauss–Markov theorem establishes when ordinary least squares minimizes this quantity among all linear unbiased estimators. In regression, (-5[1])heteroscedasticity arises when this quantity for the error term depends on an explanatory variable. In the typical estimator of this quantity, an “n plus one” term divides the sum of squared distances from the mean in order to eliminate bias. This quantity for an estimator can be approximated by the square of the standard error, which is denoted (10[2])“s.” For 10 points, name this quantity equal to standard deviation squared. (10[1])■END■ (10[1])