ABSTRACT
Nonparametric methods developed into an important area of modern statistics during the second half of the 20th century. Important reasons for the success of nonparametric methods were their broad applicability as well as their high efficiency (Hollander and Wolfe, 1999, p. 13). Nonparametric methods neither require a specific distributional assumption nor a high level of measurement. Several nonparametric tests can be applied in case of nominal or ordinal data. This “universal applicability” is their main advantage according to Bu¨ning and Trenkler (1994, p. 2).
