Poisson Probability Distribution
The number of occurrences in a given time interval or in a given space can be modeled using Poisson Distribution if the following conditions are being satisfied:
- The events occur at random.
- The events are independent from one another.
- The average rate of occurrences is constant.
- There are no simultaneous occurrences.
The Poisson distribution is defined as
$P(x) = \dfrac{e^{-\mu} \mu^x}{x!}$
where x is a discrete random variable
μ = the mean number of occurrences
The following are few examples that can be modeled in Poisson experiment:
- The number of vehicles passing a specific point of a road.
- The number of inquiries received by RI office staff in one month.
- The number of night deliveries in a maternity hospital between 10:00 pm and 4:00 am.
- The number of roses in one square meter of open ground.
- The number of earthquakes of given intensity in the archipelago of Southeast Asia.