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<h3 class="section">19.36 The Hypergeometric Distribution</h3>
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<p><a name="index-hypergeometric-random-variates-1690"></a>
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— Function: unsigned int <b>gsl_ran_hypergeometric</b> (<var>const gsl_rng * r, unsigned int n1, unsigned int n2, unsigned int t</var>)<var><a name="index-gsl_005fran_005fhypergeometric-1691"></a></var><br>
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<blockquote><p><a name="index-Geometric-random-variates-1692"></a>This function returns a random integer from the hypergeometric
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distribution. The probability distribution for hypergeometric
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where C(a,b) = a!/(b!(a-b)!) and
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<!-- {$t \leq n_1 + n_2$} -->
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t <= n_1 + n_2. The domain of k is
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<!-- {$\hbox{max}(0,t-n_2), \ldots, \hbox{min}(t,n_1)$} -->
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max(0,t-n_2), ..., min(t,n_1).
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<p>If a population contains n_1 elements of “type 1” and
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n_2 elements of “type 2” then the hypergeometric
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distribution gives the probability of obtaining k elements of
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“type 1” in t samples from the population without
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</p></blockquote></div>
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— Function: double <b>gsl_ran_hypergeometric_pdf</b> (<var>unsigned int k, unsigned int n1, unsigned int n2, unsigned int t</var>)<var><a name="index-gsl_005fran_005fhypergeometric_005fpdf-1693"></a></var><br>
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<blockquote><p>This function computes the probability p(k) of obtaining <var>k</var>
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from a hypergeometric distribution with parameters <var>n1</var>, <var>n2</var>,
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<var>t</var>, using the formula given above.
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</p></blockquote></div>
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— Function: double <b>gsl_cdf_hypergeometric_P</b> (<var>unsigned int k, unsigned int n1, unsigned int n2, unsigned int t</var>)<var><a name="index-gsl_005fcdf_005fhypergeometric_005fP-1694"></a></var><br>
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— Function: double <b>gsl_cdf_hypergeometric_Q</b> (<var>unsigned int k, unsigned int n1, unsigned int n2, unsigned int t</var>)<var><a name="index-gsl_005fcdf_005fhypergeometric_005fQ-1695"></a></var><br>
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<blockquote><p>These functions compute the cumulative distribution functions
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P(k), Q(k) for the hypergeometric distribution with
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parameters <var>n1</var>, <var>n2</var> and <var>t</var>.
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</p></blockquote></div>
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