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Poisson distribution concept

DefinitionThe distribution of a count of rare events, the limit of the binomial when n is large and p small with np held at mu, with mean and variance both mu. It is the null under which retrieval slots are handed out at random, and the Poisson ceiling is its tail. Primer S, equation S.7. Also Poisson.
ExampleWith mean 0.1 the probability of a count of three or more is 0.000155, which times fifty thousand points is 7.7.
BookData Mining as Observation, draft 0.2, commit f3914f0; entry id poisson-distribution, kind concept.
Statusno ledger row names this entry. Corrections: none recorded.
Defining equation

Book equation S.7.

Assumptions and scopenone
Prior artnone recorded
Evidencenone
Reviewedsemantic review 2026-09-09; generated 2026-09-10 from records at the commits on the provenance page.

Equation

Book equation S.7.

\[\Pr[X=k]=e^{-\mu}\frac{\mu^{k}}{k!},\qquad \mathbb E[X]=\operatorname{Var}(X)=\mu.\]

Conditions

none

Ledger

none

First stated

Primer S section S.3 of Data Mining as Observation, added in draft 0.3 (2026-09-09) for the ECE 514 readers whose first courses are far behind. The idea is standard and TSK Appendix C covers it at length.

Measurements

none

Failures and corrections

none

Invariance envelope

none declared

Machine checked

none

Used in

Data Mining as Observation primer S, chapters 0, 3, 5.

Related

Poisson ceiling; Bernoulli, binomial; null model; hub.

See also

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Status

Generated 2026-09-10 by encyclopedia/generate.py; book at observation-data-mining f3914f0; the commit of every record is listed in the encyclopedia’s provenance.

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