A Poisson Process is a model for a series of discrete event where the average time between events is known, but the exact timing of events is random. ${P(X-x)}$ = Probability of x successes. You have observed that the number of hits to your web site occur at a rate of 2 a day. You observe that the number of telephone calls that arrive each day on your mobile phone over a … In this tutorial, you learned about how to use Poisson approximation to binomial distribution for solving numerical examples. }$ Where − ${m}$ = Probability of success. Solved Example Poisson distribution examples. The arrival of an event is independent of the event before (waiting time between events is memoryless).For example, suppose we own a website which our content delivery network (CDN) tells us goes down on average once per … The Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant rate and independently of the time since the last event. e is the base of logarithm and e = 2.71828 (approx). Poisson Process. If however, your variable is a continuous variable e.g it ranges from 1