Poisson distribution: Difference between revisions

From ACT Wiki
Jump to navigationJump to search
imported>Doug Williamson
m (Spacing.)
imported>Doug Williamson
m (Correct typo "fully", remove reference to future intended edits, add comma.)
Line 3: Line 3:
A probability model used where discrete events occur in an apparently random manner, subject to an observable average rate.
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.
This rate parameter is the only parameter required to specify fully 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.
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.





Revision as of 14:03, 4 September 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 fully 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.


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