A random variable whose values are not countable is called a continuous random variable. A continuous random variable is a random variable that can assume any value contained in one or more intervals. Because the number of values contained in any interval is infinite, the possible number of values that a continuous random variable can assume is also infinite (Mann 2012).

There exist many more continuous probability distributions than we may discuss here. However, be aware that R has by now implemented a large variety of different discrete and continuous probability distributions see here. In R probability functions are accessible by generic prefixes, such as r, d, p, and q. The r is the generic prefix for random variable generator such as runif(), for the uniform distribution or rnorm(), for the normal distribution. The d is the generic prefix for the probability density function such as dunif() and dnorm(). The p is the generic prefix for the cumulative density function such as punif() and pnorm(). The q is the generic prefix for the quantile function such as qunif() and qnorm(). Keep that in mind, when we further explore the capacities in R.