Central Limit Theorem

The Central Limit Theorem says that, with more observations, a distribution appears to look more and more like a Normal Curve (bell-shaped). With too few observations, the curve is too flat and we can't assume Normality, which means we cannot use Normalcdf.

The AP Stats rule is that, if the population standard deviation is known and if n>= 30 observations, then we can assume that the distribution takes a Normal Shape. If n is fewer than 30, then we can't use the Normal Distribution. We will have to use something called the t-distribution, which we won't go over until the beginning of next year.