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Download a pdf copy of this help file here |
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Download a pdf copy of this help file here |
In many problems involving a Poisson
process, we need to determine a Poisson rate or intensity (e.g. expected
number of car crashes in a year, or concentration of particles suspended
in a liquid). To do so, you will have had some observations a in a certain
amount of exposure t. For example:
a = counted particles t = amount of liquid looked at
a = car crashes t = amount of time in which crashes occurred
a = typing errors t = amount of text reviewed
This section described three methods:
The crudest method, not recommended, but explained so you know why to avoid it.
Normal approximation to the Poisson distribution method
Commonly used. It offers some improvement over the Poisson distribution method, but still cannot be applied when a = 0, and gives incorrect results at extremes.
Cumulative confidence construction
The best method that works for all values of a and t. It is also closely aligned to Bayesian results.