For a discrete distribution, probabilities can be assigned to the values in the distribution – for example, “the probability that the web page will have 12 clicks in an hour is 0.15.”  In contrast, a continuous distribution has an infinite number of possible values, and the probability associated with any particular value of a continuous distribution is null. Therefore, continuous distributions are normally described in terms of probability density, which can be converted into the probability that a value will fall within a certain range.