This quantity is given by "n divided by n minus 1 times the sum of the squares of the estimated differences" in the jackknife method. For the central limit theorem to apply, this quantity, which is on
This quantity is given by "n divided by n minus 1 times the sum of the squares of the estimated differences" in the jackknife method. For the central limit theorem to apply, this quantity, which is one of the moments of a distribution, must be finite. For the binomial distribution, this quantity is defined as the number of trials, times the probability p of the trial, times one minus p; that is because this quantity is defined as the expected (*) value of the square of a random variable minus the square of the expected value of the random variable. Stratified sampling is one way to decrease this quantity, which tends towards 0 as n gets large. The square of the standard deviation is, for 10 points, what measure of how much a distribution is "spread out?"
This quantity is given by "n divided by n minus 1 times the sum of the squares of the estimated differences" in the jackknife method.