Created Tuesday 07 January 2014
A gaussian distribution (aka normal distribution) is defined by the following probability density function:
`\ f(x) = 1/(sigma sqrt(2 pi)) e^(-(x-mu)^2∕(2sigma^2))`
where `mu` is the population mean and `sigma^2` is the variance.
If a random variable X follows the normal distribution, then we write:
`\ X ~ N(mu, sigma^2)`
The standard normal distribution is a special case of a normal distribution with `mu = 0` and `sigma = 1`.
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