One remarkable fact about the normal distribution is
the fact that if we took many samples of size n from
a population having mean 
and variance 
(any
distribution we want), then the population of 
's would
be approximately normally distributed with mean and variance
. The larger n is, the better the approximation is.
These facts are known collectively as the Central Limit Theorem and allow us to make inferences about population means using the normal distribution no matter what the distribution of the population being sampled from. See the ``Central Limit Theorem'' concept lab for more about this.