Poisson distribution: Difference between revisions
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imported>Doug Williamson (Amend illustration from 'phone calls received' to 'business interruptions occurring'.) |
imported>Doug Williamson (Add 'finite' before 'number' for clarity.) |
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The Poisson distribution can be a useful model for processes where: | The Poisson distribution can be a useful model for processes where: | ||
#Continuous observation is needed, rather than a number of independent trials. | #Continuous observation is needed, rather than a finite number of independent trials. | ||
#The random variable takes a positive whole number (integer) value, with no upper limit. | #The random variable takes a positive whole number (integer) value, with no upper limit. | ||
#The expected number of occurrences is known or can be estimated, and | #The expected number of occurrences is known or can be estimated, and | ||
Revision as of 11:11, 7 August 2014
Statistics.
A probability model used where discrete events occur in a continuum.
For example, the number of business interruptions occurring in a given time period.
The Poisson distribution can be a useful model for processes where:
- Continuous observation is needed, rather than a finite number of independent trials.
- The random variable takes a positive whole number (integer) value, with no upper limit.
- The expected number of occurrences is known or can be estimated, and
- Primary interest is in the number of times an event occurs within a particular period.
