ABSTRACT
A continuous random variable takes on an infinitely large number of values on the real line. There is a function that assigns probability measures to the random variable values. The probability distribution histogram enables us to calculate different probabilities. A probability density function (in the case of a continuous random variable) has different properties. Binomial distributions and geometric distributions are associated with the Bernoulli process. It is important to emphasize that geometric probability mass function has a no-memory property. This means that the number of trials carried out until the first success occurs in no way affects how many more trials will need to be carried out until the next success. Measurements in many transportation systems show that the client arrivals pattern could be described by the Poisson distribution. It has been shown that Poisson distribution describes many real-life situations.
