Applications of this theorem include justifying the use of confidence intervals on data from arbitrary distribution, and the fact that 30 is a pretty good sample size for estimating some measure of a population.
The Lindeberg condition is a weak method of finding whether this theorem holds. The speed at which this theorem's predictions will hold is of the order of n to the negative one-half if the third central moment is finite according to the Berry-Esseen theorem. This theorem is proven by noting that the characteristic function one minus one-half times t squared plus little o of t squared converges to e to the negative t squared over 2. Applications of this theorem include justifying the use of confidence intervals on data from arbitrary distribution, and the fact that 30 is a pretty good sample size for estimating some measure of a population. For 10 points, name this theorem that says that the sum of a large number of identically distributed random variables converges to a normal distribution.
The Lindeberg condition is a weak method of finding whether this theorem holds.
central limit theorem