A continuous distribution describes probabilistic properties of a random variable which takes on a continuous (not countable) set of values – a continuous random variable.
In contrast to discrete distributions, continuous distributions do not ascribe values of probability to possible values of the random variable. Strictly speaking, the probability associated with any particular value of a continuous distribution is null. Therefore, continuous distributions are normally described in terms of probability density, rather than probability.
Some examples of continuous distributions are the normal distribution, log-normal distribution, t-distribution, F-distribution.