Normal distributions generally look like this. Although their
width and center can change based on the
distribution's parameters. There are two parameters associated with
a normal distribution. The mean, mu. And the standard
deviation, sigma. These two parameters plug in to
the following probability density function, which describes a
Gaussian distribution. The expected value of a variable
described by a Gaussian distribution is the mean, mu.
and the variance is the standard deviation, sigma
squared. Normal distributions are also symmetric about their
mean. If you've taken an introduction to stats
course, the normal distribution should be a familiar tool.