Technically speaking this is sampling without replacement, so the correct distribution is the multivariate hypergeometric distribution, but the distributions converge as the population grows large ."
32.
The probability distribution when " n " is known ( but the number of each type is not known yet ) is Fisher s noncentral hypergeometric distribution.
33.
The balls that are " not " taken in the urn experiment have a distribution that is different from Wallenius'noncentral hypergeometric distribution, due to a lack of symmetry.
34.
See the entry for noncentral hypergeometric distributions for an explanation of the difference between these two distributions and a discussion of which distribution to use in various situations.
35.
In probability theory and statistics, "'Wallenius'noncentral hypergeometric distribution "'( named after Kenneth Ted Wallenius ) is a generalization of the hypergeometric distribution where items are sampled with bias.
36.
In probability theory and statistics, "'Wallenius'noncentral hypergeometric distribution "'( named after Kenneth Ted Wallenius ) is a generalization of the hypergeometric distribution where items are sampled with bias.
37.
An important application of the noncentral hypergeometric distribution in this context is the computation of exact confidence intervals for the odds ratio comparing treatment response between the two groups.
38.
The case where ordering doesn't matter and sampling is without replacement is comparable to a single multivariate hypergeometric distribution, and the fourth possibility does not seem to have a correspondence.
39.
Note also that there are some " noncentral distributions " that are not usually formulated in terms of a " noncentrality parameter " : see noncentral hypergeometric distributions, for example.
40.
The name " noncentral hypergeometric distribution " has been used for two different distributions, and several scientists have used the wrong distribution or erroneously believed that the two distributions were identical.
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