The normal distribution is an assumption of many parametric statistical tests, and is typically associated with a Gaussian distribution, often with mean=0 and standard deviation=1. The "bell curve" is the visual, intuitive model for this distribution. Gaussian distributions are associated with the function: f(x) = [1/(σ√2π)] e^(-[(x-μ)^2]/(2σ^2 ))
In scientific software r for statistical computing and graphics, we can use dnorm function to compute density of a normal distribution, rnorm function to generate random samples from a normal distribution, pnorm function to compute CDF of a normal distribution and qnorm function to compute quantiles of a normal distribution.
