Poisson Distribution Calculator

Modeling Events That Arrive at a Steady Average Rate

Some things don't have a natural "number of trials" — calls arriving at a support line, customers entering a store, typos on a page. What they do have is an average rate over a given interval, and that's all the Poisson distribution needs to work out the probability of seeing exactly, at most, or at least a given count in that same interval.

The Formula

P(X = k) = (e^−λ × λ^k) ÷ k!

λ (lambda) is the average number of occurrences in the interval, and k is the specific count you're evaluating. Both the mean and the variance of a Poisson distribution equal λ.

Worked Example: Call Center Volume

A support line averages 4 calls per hour. The probability of receiving exactly k calls in the next hour:

Poisson distribution, λ = 4 calls/hour
Calls (k)Probability
01.83%
17.33%
214.65%
319.54%
419.54%
515.63%
610.42%

The probability of 2 or fewer calls in the hour is 23.81%, while the probability of 6 or more is 21.49% — useful for staffing decisions even though 4 is the "expected" figure.

Where This Matters

  • Staffing and operations — call centers, emergency rooms, and service counters use Poisson models to plan for demand variability, not just the average.
  • Reliability engineering — modeling the number of equipment failures expected in a given time period.
  • Epidemiology — modeling rare disease case counts across a population and time period.
  • Network and queueing theory — packet arrivals, server requests, and similar arrival processes are classic Poisson applications.

How to Use This Calculator

  1. Choose Exactly, At Most, or At Least K Occurrences from the dropdown.
  2. Enter the average rate (λ) for the interval you're analyzing.
  3. Enter the number of occurrences (k) you're interested in.
  4. Select Calculate to get the probability.

Related Calculations

For the time between Poisson-distributed events rather than the count itself, see the Exponential Distribution Calculator. For fixed-trial success counts instead of rate-based events, use the Binomial Distribution Calculator.