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POISSON

Description: Returns the Poisson distribution. A common application of the Poisson distribution is predicting the number of events over a specific time, such as the number of cars arriving at a toll plaza in 1 minute.

Syntax: POISSON(x, Lambda, Cumulative)

• x is the number of events.

• Lambda is the expected numerical value.

• Cumulative is a logical value that determines the form of the probability distribution returned. If Cumulative is TRUE, POISSON returns the cumulative Poisson probability that the number of random events occurring will be between 0 and x inclusive; if FALSE, it returns the Poisson probability mass function that the number of events occurring will be exactly x.

Remarks:

• x must be an integer.

• x and Lambda must be numeric.

• x and Lambda must be > 0.

• POISSON is calculated as follows.

• For Cumulative = FALSE:

• For Cumulative = TRUE:

Example:

• POISSON(2,5,TRUE) = 0.124652

• POISSON(2,5,FALSE) = 0.084224