Eksakttest

Eksakttest, also known as an exact test, is a statistical method used to determine the significance of the difference between two groups or conditions. Unlike parametric tests, which assume a specific distribution of the data, eksakttest does not rely on such assumptions. This makes it particularly useful when dealing with small sample sizes or non-normally distributed data.

The most common type of eksakttest is the Fisher's Exact Test, which is used for categorical data, particularly in 2x2 contingency tables. This test calculates the exact probability of obtaining the observed data or something more extreme, given the null hypothesis. It is particularly useful when the expected frequencies in the cells of the contingency table are small, as it avoids the approximations used in the chi-square test.

Another type of eksakttest is the Wilcoxon Signed-Rank Test, which is a non-parametric alternative to the paired t-test. This test ranks the differences between paired observations and then tests whether the sum of the ranks is significantly different from what would be expected under the null hypothesis.

Eksakttest is widely used in various fields, including biology, medicine, and social sciences, where the assumptions of parametric tests may not hold. However, it is important to note that eksakttest can be computationally intensive, especially for large datasets, and may not be suitable for all types of data.