The 1 Parameter Poisson Distribution 4 Formulas

The 1 Parameter Poisson Distribution 4 Formulas

This is part of a short series on the common life data distributions.

The Poisson distribution is a discrete distribution. This short article focuses on 4 formulas of the Poisson Distribution. It is also known as the rare event distribution. It has application in a homogeneous Poisson princess and with renewal theory.

Check the following conditions to verify the process follows a Poisson distribution:

• There is a negligible or impossible chance of two simultaneous events.
• The expected value of vents in a region is proportional to the size of the region.
• The events in non-overlapping regions are independent.

If you want to know more about fitting a set of data to a distribution, well that is in another article.

It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions.

Parameters

The shape parameter, μ, is the expected number of event per time period. If modeling…