Fisher's Exact Test
Fisher's Exact Test is a statistical method used to determine if there are nonrandom associations between two categorical variables, typically in small sample sizes. For example, imagine you want to know if a specific medication is more effective for men than women. This test helps calculate the probability of observing the data you have, assuming there is no actual difference. It’s particularly useful when traditional methods, like chi-squared tests, may not be reliable due to small numbers in some categories, ensuring valid conclusions about associations between groups.
Additional Insights
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Fisher's Exact Test is a statistical method used to determine if there are significant associations between two categorical variables, especially in small sample sizes. For example, if you want to see if a medicine affects patient recovery differently for men and women, this test can help analyze the data in a 2x2 table (e.g., recovered vs. not recovered for each gender). It calculates the probability of observing the data under the assumption that there is no real effect, helping researchers decide if the differences observed are likely due to chance or if they reflect a true relationship.