What is fisher testi?

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Fisher testing, also known as Fisher's exact test, is a statistical significance test used to analyze the association between two categorical variables. It is often used in small sample sizes, where the assumptions of large sample sizes are not valid. The Fisher test calculates the probability of observing a set of data given a null hypothesis.

The Fisher test is commonly used in scientific research where it is required to measure an association between two variables or compare the observations of two populations. It is also used to identify the significance of an agreement or disagreement between two sets of data.

The Fisher test is based on the hypergeometric distribution, which is used to calculate the probability of obtaining a certain set of results from a population with a specific number of successes and failures. In the context of Fisher testing, the results of interest are the frequency of data in a contingency table.

The Fisher test is considered more accurate than the chi-squared test in small sample sizes, as the chi-squared test assumes that the sample is large enough to allow for normally distributed values to be used.

In summary, Fisher testing is a statistical test used to analyze the relationship between two categorical variables in small sample sizes. It is based on the hypergeometric distribution and is commonly used in scientific research for association and comparison analysis.