The rnorm() function in R is a convenient way to simulate values from the normal distribution, characterized by a given mean and standard deviation. I hadn’t previously used the associated commands dnorm() (normal density function), pnorm() (cumulative distribution function), and qnorm() (quantile function) before– so I made a simple demo. The *norm functions generate results based on a well-behaved normal distribution, while the corresponding functions density(), ecdf(), and quantile() compute empirical values. The following example could be extended to graphically describe departures from normality (or some other distribution– see rt(), runif(), rcauchy() etc.) in a data set.