| 1. | For more details, see the article on the Poisson distribution.
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| 2. | Then the distribution may be approximated by the less cumbersome Poisson distribution
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| 3. | A more precise estimate is obtained by applying the Poisson distribution.
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| 4. | A Poisson distribution is discrete, a Gaussian distribution is continuous.
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| 5. | The Poisson distribution in probability theory is named after him.
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| 6. | The distribution may be modeled using a Zero-truncated Poisson distribution.
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| 7. | The expected distribution can be found using Poisson distribution.
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| 8. | Is there a formal test for whether a variable follows a Poisson Distribution?
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| 9. | Since the problem is essentially continuous, the Poisson distribution is completely irrlevant.
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| 10. | The actual number of times has a poisson distribution.
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