1.5 KiB
Fisher Exact Test
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Questions to David Rotermund
scipy.stats.fisher_exact
scipy.stats.fisher_exact(table, alternative='two-sided')
Perform a Fisher exact test on a 2x2 contingency table.
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.
alternative : {‘two-sided’, ‘less’, ‘greater’}, optional Defines the alternative hypothesis. The following options are available (default is ‘two-sided’):
- ‘two-sided’: the odds ratio of the underlying population is not one
- ‘less’: the odds ratio of the underlying population is less than one
- ‘greater’: the odds ratio of the underlying population is greater than one
See the Notes for more details.