When the total sample size is small, it is necessary to use an appropriate exact test, typically either the binomial test or ( for contingency tables ) Fisher's exact test.
32.
For very small samples the multinomial test for goodness of fit, and Fisher's exact test for contingency tables, or even Bayesian hypothesis selection are preferable to the " G "-test.
33.
The " G "-test, Fisher's exact test, and Barnard's test, provided the entries in the table represent individuals randomly sampled from the population about which we want to draw a conclusion.
34.
For example, in computational geometry, exact tests of whether a point lies off or on a line or plane defined by other points can be performed using adaptive precision or exact arithmetic methods.
35.
The statistical significance of the overlap between genes from a pathway and the list of differently expressed genes is determined by such statistical tests as Fisher's exact test, Hypergeometric distribution test or Jaccard index.
36.
A test that relies on different assumptions is Fisher's exact test; if its assumption of fixed marginal distributions is met it is substantially more accurate in obtaining a significance level, especially with few observations.
37.
For data with small sample size, such as no marginal total is greater than 15 ( and consequently N \ le 30 ), one should utilize Yates's correction for continuity or Fisher's exact test.
38.
While conventional statistical methods do not provide exact solutions to such problems as testing variance components or ANOVA under unequal variances, exact tests for such problems can be obtained based on generalized " p "-values.
39.
In this book Fisher also outlined the Lady tasting tea, now a famous design of a statistical randomized experiment which uses Fisher's exact test and is the original exposition of Fisher's notion of a null hypothesis.
40.
It also initiated the addition of exact-test options in the main statistical software packages and the appearance of specialized software for performing a wide range of uni-and multi-variable exact tests and computing test-based " exact " confidence intervals.
