Suppose X is a random variable that is binomially distributed with probability of success λ/n and number of trials n, that is X∼B(n,λ/n). The probability that X takes a special value x is then given by:P(X=x)=(nx)(λn)x(1−λn)n−x
This can be written as:P(X=x)=n(n−1)(n−2)...(n−x+1)x!×λxnx(1−λn)n−x
Again, this can be rearranged to:P(X=x)=λxx!×n−1n×n−2n×...×n−x+1n×(1−λn)n−x
An n→∞, the expression becomes: P(X=x)=λxx!e−λ
This formula then represents the Poisson distribution, a suitable model for events which:
- occur randomly in space or time
- occur singly, that is events cannot occur simultaneously
- occur independently
- occur at a constant rate, that is a mean number of events in a given time interval is proportional to the size of the interval
A discrete random variable that follows a Poisson distribution with parameter λ is written as X∼Po(λ) and the mean of this distribution is λ and the variance is also λ. Thus the mean and variance of a Poisson distribution are equal.
In Google Sheets, the syntax for the Poisson distribution function is shown below:
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