Hypergeometric Distribution: Difference between revisions
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This describes many systems, most notably a deck of 52 [[Cards]] and dealing e.g. poker hands. | This describes many systems, most notably a deck of 52 [[Cards]] and dealing e.g. poker hands. | ||
Hypergeometric distribution: | |||
<math> | |||
\dfrac{ | |||
\binom{K}{k} \binom{N-K}{n-k} | |||
}{ | |||
\binom{N}{n} | |||
} | |||
</math> | |||
wehere: | |||
<math> | |||
\begin{align} | |||
K &=& \mbox{Number of successful trials} \\ | |||
N &=& \mbox{Popullation size} \\ | |||
k &=& \mbox{Number of targets counting as success for trials} \\ | |||
n &=& \mbox{Sample size} | |||
\end{align} | |||
</math> | |||
Revision as of 21:27, 9 March 2019
Hypergeometric distribution counts the number of ways you can obtain particular target values when sampling from a population without replacement.
This describes many systems, most notably a deck of 52 Cards and dealing e.g. poker hands.
Hypergeometric distribution:
$ \dfrac{ \binom{K}{k} \binom{N-K}{n-k} }{ \binom{N}{n} } $
wehere:
$ \begin{align} K &=& \mbox{Number of successful trials} \\ N &=& \mbox{Popullation size} \\ k &=& \mbox{Number of targets counting as success for trials} \\ n &=& \mbox{Sample size} \end{align} $