The Poisson distribution named after French mathematician Siméon Denis Poisson (1781-1840).
is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time and/or space if these events occur with a known average rate and independently of the time since the last event
Examples of the Poisson distribution are: the number of cars passing in a certain place during one hour, number of phone calls etc.
Probability of events for a Poisson distribution
An event can occur 0, 1, 2, … times in an interval. The average number of events in an interval is designated (lambda). Lambda is the event rate, also called the rate parameter. The probability of observing k events in an interval is given by the equation
is the average number of events per interval
e is the number 2.71828... (Euler's number) the base of the natural logarithms
k takes values 0, 1, 2, …
k! = k × (k − 1) × (k − 2) × … × 2 × 1 is the factorial of k.
For example: Salesman sales, in average, 5 products per week. The chance he will sale, in a given week 10 products is 1.8133%