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Poisson distribution

[ pwah-sohn; French pwa-sawn ]

noun

, Statistics.
  1. a limiting form of the binomial probability distribution for small values of the probability of success and for large numbers of trials: particularly useful in industrial quality-control work and in radiation and bacteriological problems.


Poisson distribution

/ ˈpwɑːsən /

noun

  1. statistics a distribution that represents the number of events occurring randomly in a fixed time at an average rate λ ; symbol P 0 ( λ ). For large n and small p with np = λ it approximates to the binomial distribution Bi ( n,p )
“Collins English Dictionary — Complete & Unabridged” 2012 Digital Edition © William Collins Sons & Co. Ltd. 1979, 1986 © HarperCollins Publishers 1998, 2000, 2003, 2005, 2006, 2007, 2009, 2012


Poisson distribution

/ pwä-sôn /

  1. A probability distribution which arises when counting the number of occurrences of a rare event in a long series of trials. It is named after its discoverer, French mathematician and physicist Siméon Denis Poisson (1781–1840).


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Word History and Origins

Origin of Poisson distribution1

1920–25; named after S. D. Poisson (1781–1840), French mathematician and physicist
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Word History and Origins

Origin of Poisson distribution1

C19: named after S. D. Poisson
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Example Sentences

The Poisson distribution is a statistics term that formally describes a situation described above, wherein events occur at a constant rate and independently of previous events.

From Salon

The pattern of direct communication in larger teams looks like a Poisson distribution: one, sometimes two members, do the lion’s share of the talking.

Compared with a Poisson distribution expected for adaptive mutations, this Luria–Delbrück distribution has a long ‘tail’ at the end of the distribution pattern.

From Nature

To derive his equation, Dr Grimes began with the Poisson distribution, a common statistical tool that measures the probability of a particular event occurring over a certain amount of time.

From BBC

However, Barnett also draws attention to the theory of Poisson distribution, which implies that short intervals between crashes are actually more probable than long ones.

From BBC

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