Central Limit Theorem Simulator

The Central Limit Theorem is the reason statistical inference works at all: no matter how strange the underlying population looks, the average of enough independent draws from it behaves like a normal distribution. This simulator draws repeated samples of size n from a uniform, exponential or bimodal source, computes each sample's mean, and bins the results live into a 3D histogram with the theoretical normal curve overlaid. Shrink or grow n and switch source distributions to see how quickly — or slowly — real-world data of any shape settles into the bell curve that hypothesis tests and confidence intervals rely on.