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Poisson Distribution Calculator

Calculate Poisson probabilities for rare events. Find P(X = k), P(X ≤ k), and P(X > k) given an average rate λ.

P(X = 4)
0.168031
P(X ≤ 4)0.815263
P(X > 4)0.184737
Mean (λ)3
Variance (λ)3
Std dev (√λ)1.7321

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How to use this calculator

P(X = k) = (λᵏ · e⁻λ) / k!

λ is the average number of events in the interval. k is the specific count of interest. e is Euler's number (~2.71828).

  1. 1

    Enter λ (lambda): the average number of events per interval (e.g. 3 calls per minute).

  2. 2

    Enter k: the specific count you want the probability for (e.g. exactly 4 calls).

  3. 3

    The calculator returns P(X = k), the cumulative P(X ≤ k), and P(X > k).

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Frequently asked questions

What is the Poisson distribution used for?

The Poisson distribution models the number of independent events that occur in a fixed interval of time or space, when the average rate is known. Examples: call centre arrivals per minute, defects per product, accidents per year.

When does the Poisson distribution apply?

Use it when: events are independent; the rate is constant; two events cannot occur at exactly the same instant; and you're counting discrete events in a fixed interval.

How is Poisson different from binomial?

The binomial distribution models a fixed number of trials with probability p. The Poisson distribution models an unlimited number of possibilities with a small individual probability — it is the limiting case of the binomial as n → ∞ and p → 0 with λ = np fixed.

About poisson distribution calculator

Poisson Distribution Calculator — P(X=k) & Cumulative Probability

Understanding the Poisson distribution

Named after Siméon Denis Poisson, this discrete probability distribution predicts the number of events in a fixed period when events happen at a constant average rate and independently of each other. Classic applications include queuing theory, insurance modelling, nuclear decay, and epidemiology.

Mean and variance of Poisson

A distinctive property of the Poisson distribution is that its mean and variance are both equal to λ. This makes it easy to estimate λ from data: just compute the sample mean. If the sample variance is much larger than the mean (overdispersion), a negative binomial distribution may be more appropriate.

Poisson Distribution Calculator – Utinzo

Learn more from an authoritative source:

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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →