Poisson Distribution Calculator

The Poisson distribution gives the chance of seeing a number of events in a fixed interval when they arrive independently at a steady average rate. Enter lambda, the mean number of events in that interval, and a count, and it returns the probability of exactly that count together with the totals above and below it. A second action builds lambda from a rate and an interval length, and a third adds up a whole range of counts. Every probability is computed in logarithms, so a count in the hundreds does not overflow. The answer assumes the rate never changes and that events do not arrive in clusters, which is where real data usually parts company with the model.

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Lambda is the average number of events in the interval you care about, not a rate per minute unless the interval is a minute.

The historical average for an interval of the same length as the one you are asking about.
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Enter the rate in events per unit of time and how many units the interval runs for. Lambda is the two multiplied together.

Calls per hour, arrivals per minute, defects per metre. The unit is whatever you say it is.
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The chance the count lands anywhere between two values, both ends included.

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