The central limit theorem states that the mean of sufficiently large independent samples is approximately normally distributed, whatever the shape of the original distribution. This mean is centered on the population mean, with a standard deviation equal to sigma divided by the square root of n. It justifies confidence intervals and many tests.
Example
Repeated means of die rolls, each computed over 50 rolls, form a bell curve centered on 3.5.