One informal description of insanity is “repeating the same action while expecting a different result.” By this notion, the act of simulating a distribution could be considered somewhat insane, as it involves repeatedly sampling from a distribution and investigating the differences in the results. But simulating a distribution is far from insane. Simulating a distribution can give us great insight into the distribution’s shape, its tails, its mean and variance, etc. We’ll use simulation to justify the size of n needed in the central limit theorem for approximate normality of the sample mean. Simulation is useful with such specific questions, as well as with those of a more exploratory nature.