Poisson Sampling Algorithm
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A Poisson Sampling Algorithm is a Sampling Algorithm where each element of the population that is sampled is subjected to an independent Bernoulli trial which determines whether the element becomes part of the sample during the drawing of a single sample.
- See: Finite Population Sampling, Sampling (Statistics), Statistical Population, Statistical Independence, Bernoulli Trial, Inclusion Probability, Bernoulli Sampling.
References
2014
- (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/Poisson_sampling Retrieved:2014-8-26.
- In the theory of finite population sampling, Poisson sampling is a sampling process where each element of the population that is sampled is subjected to a independent Bernoulli trial which determines whether the element becomes part of the sample during the drawing of a single sample.
Each element of the population may have a different probability of being included in the sample. The probability of being included in a sample during the drawing of a single sample is denoted as the first-order inclusion probability of that element. If all first-order inclusion probabilities are equal, Poisson sampling becomes equivalent to Bernoulli sampling, which can therefore be considered to be a special case of Poisson sampling.
- In the theory of finite population sampling, Poisson sampling is a sampling process where each element of the population that is sampled is subjected to a independent Bernoulli trial which determines whether the element becomes part of the sample during the drawing of a single sample.