aparametrisch

Aparametrisch is a German adjective that translates to "non-parametric" in English. It is primarily used in statistics and mathematics to describe methods or models that do not rely on specific assumptions about the underlying distribution of the data. Unlike parametric methods, which assume that the data follows a particular distribution (e.g., a normal distribution), non-parametric methods are more flexible and can be applied to a wider range of data types and distributions. These methods often work directly with the observed data or its ranks, making fewer assumptions about population characteristics. Examples of non-parametric statistical tests include the Mann-Whitney U test and the Wilcoxon signed-rank test, which are used to compare groups without assuming normality. In the context of modeling, non-parametric approaches can include techniques like kernel density estimation or decision trees, which do not impose a predefined functional form on the relationship between variables. The term aparametrisch therefore signifies a lack of restrictive distributional assumptions.