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.