Important Formulas on Poisson Distribution

The table below represents the important formulas of Poisson distribution.

Where,

• ƛ is Mean
• x is Number of Required Outcomes
• n is Total Number of Trials
• p is Probability of Success
• Var(X) is Variance
• σ is Standard Deviation

Poisson distribution is a probability distribution that models the number of events occurring within a fixed interval of time or space, where these events happen with a known constant mean rate and independently of the time since the last event. It is named after the French mathematician Siméon Denis Poisson.

Suppose a call center receives an average of 10 calls per hour. We can model the number of calls received in a given hour using a Poisson distribution with λ = 10. There are many scenarios that can be modelled with the help of Poisson Distribution. Some of these scenarios are:

• An intersection has an average of 3 cars passing through every minute.
• A factory produces 1000 widgets per day, with an average of 2 defective widgets.
• A website gets an average of 50 hits per minute.
• In a strand of DNA, an average of 0.3 mutations occur per unit length.

This article has covered practice questions on Poisson Distribution with solutions in detail.