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.
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.
variance