Poisson distribution: Difference between revisions

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imported>Doug Williamson
(Amend from 'useful' model to 'appropriate'.)
imported>Brianlenoach@hotmail.co.uk
m (flesh out the basic definition,s show the value and use of the Poisson distriburtion)
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<i>Statistics</i>.
<i>Statistics</i>.


A probability model used where discrete events occur in a continuum.
A probability model used where discrete events occur in an apparently random manner, subject to an observable average rate.
 
This rate parameter is the only parameter required to specify full the probability distribution function of a Poisson random variable.
For example, the number of business interruptions occurring in a given time period.
For example, the number of business interruptions occurring in a given time period or the number of admissions to a hospital A & E department in a given time period. We intend to return to the latter example in a future editing session.
 


The Poisson distribution can be an appropriate model for processes where:
The Poisson distribution can be an appropriate model for processes where:

Revision as of 10:38, 28 August 2014

Statistics.

A probability model used where discrete events occur in an apparently random manner, subject to an observable average rate. This rate parameter is the only parameter required to specify full the probability distribution function of a Poisson random variable. For example, the number of business interruptions occurring in a given time period or the number of admissions to a hospital A & E department in a given time period. We intend to return to the latter example in a future editing session.

The Poisson distribution can be an appropriate model for processes where:

  1. Continuous observation is needed, rather than a finite number of independent trials.
  2. The random variable takes a positive whole number (integer) value, with no upper limit.
  3. The expected number of occurrences is known or can be estimated, and
  4. Primary interest is in the number of times an event occurs within a particular period.


See also