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Poisson Distribution Formula

About Poisson Distribution Formula

The Poisson distribution, often known as the Poisson distribution probability mass function, is a theoretical discrete probability. It is used to calculate the probability of an independent event recurring at a steady mean rate over a specific time frame. Other fixed intervals, such as volume, area, and distance, can also be employed with the Poisson distribution probability mass function. If there are few successes across many attempts, a Poisson random variable will fairly capture the occurrence. When the trials are indefinitely large, the Poisson distribution is utilised as a limiting case of the binomial distribution. When a Poisson distribution is used to simulate the identical binomial phenomena, np is used instead. The Poisson distribution is named after Denis Poisson, a French mathematician. Get the List of all Maths formulas in one place.

What is Poisson Distribution?

The Poisson distribution definition is used to model a discrete probability of an event in which independent occurrences occur at a known constant mean rate over a specified length of time. In other words, the Poisson distribution is used to predict how many times an event will occur during a certain time period. is the Poisson rate parameter, which represents the expected number of events in a given time frame.

Poisson Distribution Formula

When the mean rate of occurrence is constant throughout time, the Poisson distribution formula is used to calculate the chance of an event occurring independently, discretely over a specified time period. When there are a vast number of alternative outcomes, the Poisson distribution formula is used.

The probability of a random discrete variable X that follows the Poisson distribution and is the average rate of value is given by:

  • f(x) = P(X=x) = (e λx )/x!
  • Here, x = 0, 1, 2, 3...
  • e is Euler's number(e = 2.718) and
  • λ is an average rate of the expected value and λ = variance, also λ>0

Poisson Distribution Mean and Variance

The mean of the Poisson distribution and the value of variance will be the same for a fixed interval of time for a Poisson distribution with as the average rate. So, for X with a Poisson distribution, we may state that is the distribution's mean as well as variance.

Hence: E(X) = V(X) = λ

Here, E(X) is the expected mean, V(X) is the variance, λ > 0

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