34 lines
1.5 KiB
Markdown
34 lines
1.5 KiB
Markdown
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# Fisher Exact Test
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{:.no_toc}
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<nav markdown="1" class="toc-class">
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* TOC
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{:toc}
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</nav>
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## Top
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Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
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## [scipy.stats.fisher_exact](https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.fisher_exact.html)
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```python
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scipy.stats.fisher_exact(table, alternative='two-sided')
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```
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> Perform a Fisher exact test on a 2x2 contingency table.
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>
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> The null hypothesis is that the true odds ratio of the populations underlying the observations is one, and the observations were sampled from these populations under a condition: the marginals of the resulting table must equal those of the observed table. The statistic returned is the unconditional maximum likelihood estimate of the odds ratio, and the p-value is the probability under the null hypothesis of obtaining a table at least as extreme as the one that was actually observed. There are other possible choices of statistic and two-sided p-value definition associated with Fisher’s exact test; please see the Notes for more information.
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> **alternative** : {‘two-sided’, ‘less’, ‘greater’}, optional
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> Defines the alternative hypothesis. The following options are available (default is ‘two-sided’):
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>
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> * ‘two-sided’: the odds ratio of the underlying population is not one
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> * ‘less’: the odds ratio of the underlying population is less than one
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> * ‘greater’: the odds ratio of the underlying population is greater than one
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See the Notes for more details.
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