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 by now a large variety of different
discrete and continuous probability distributions are implemented in R
(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
dnorm(). The p is the generic prefix for
the cumulative density function such as
pnorm(). The q is
the generic prefix for the quantile function such as
qnorm(). Keep that in mind, while
we further explore the capacities in R.
The following functions and R-packages are used in this section (in alphabetical order):
The E-Learning project SOGA-R was developed at the Department of Earth Sciences by Kai Hartmann, Joachim Krois and Annette Rudolph. You can reach us via mail by soga[at]zedat.fu-berlin.de.
Please cite as follow: Hartmann, K., Krois, J., Rudolph, A. (2023): Statistics and Geodata Analysis using R (SOGA-R). Department of Earth Sciences, Freie Universitaet Berlin.