The central limit theorem states that the sum of a large number of independent observations from the same distribution has, under certain general conditions, an approximate normal distribution.
The accuracy of the approximation depends on the number of summands (choose a large N) and the shape of the intial distribution. The approximation works best for symmetric distributions (try a probability around .50).

Other things to do:
Galton Board
Central limit theorem and the Poisson distribution