law of rare events


Let X be distributed as B⁢i⁢n⁢(n,p), a binomial random variableMathworldPlanetmath with parameters n and p. Suppose

limn→∞⁡n⁢p=λ,

where λ is a positive real constant, then X is asymptotically distributed as P⁢o⁢i⁢s⁢s⁢o⁢n⁢(λ), a Poisson distributionMathworldPlanetmath with parameter λ.

Basically, when the size of the population n is very large and the occurrence of certain event A is rare, where p, the probability of A is very small, the binomial random variable X can be approximated by a Poisson random variable.

Sketch of Proof. Let X∼B⁢i⁢n⁢(n,p). So

P(X=m) = n!m!⁢(n-m)!⁢pm⁢(1-p)n-m
= n!nm⁢(n-m)!⁢(n⁢p)mm!⁢(1-n⁢pn)n-m
= n!nm⁢(n-m)!⁢(n⁢p)mm!⁢(1-n⁢pn)n⁢(1-n⁢pn)-m.

As n→∞,

n!nm⁢(n-m)!=nn⁢n-1n⁢⋯⁢n-m+1n≈1,
(1-n⁢pn)-m≈(1-λn)-m≈1,
(1-n⁢pn)n≈(1-λn)n≈e-λ,

and

(n⁢p)mm!≈λmm!.

Therefore,

P(X=m)≈λmm!e-λ=Poisson(λ).

Example. Suppose in a given year, the number of fatal automobile accidents has a binomial distribution for a particular insuarance company with five hundred automobile insurance policies. On average, there is one policy out of the five hundred that will be involved in a fatal crash. What is the probability that there will be no fatal accidents (out of five hundred policies) in any particular year?

Solution. If X be the number of fatal accidents in a year from a population of 500 auto policies, then X∼B⁢i⁢n⁢(n,p) with n=500 and p=1/500. λ=500×1/500=1 and so

P(X=0)≈e-1≈0.368.

Using the binomial distribution, we have

P(X=0)=(1-1500)500≈0.367.
Title law of rare events
Canonical name LawOfRareEvents
Date of creation 2013-03-22 14:39:32
Last modified on 2013-03-22 14:39:32
Owner CWoo (3771)
Last modified by CWoo (3771)
Numerical id 6
Author CWoo (3771)
Entry type Definition
Classification msc 62P05
Classification msc 60E99
Classification msc 60F99
Synonym Poisson theorem