Application of non-parametric tests of significance to the market analyses

Common using of parametric tests to elaborate research results is limited by predetermined assumptions (variable measurability, normality of its distribution, homogeneity of database etc), which must be fulfilled. Otherwise, the conclusions obtained by calculating using a parametric test will not be quite correct. Parametric tests are useless also in the case of the quality data and the data of a purely ordinal nature. In such situations, we use the tests nonparametric. These tests are not dependent on the parameters of population distribution. The calculation formulas are simple, and the calculations do not take much time. Therefore, we can employ them widely, when the assumptions required for parametric tests are not fulfilled. Moreover, we use them, when our data may be arranged according to determined criteria and for some random samples of small size. The power of the non-parametric tests (equal to one minus the magnitude of the type 2 error) is however lower than the power of the parametric tests. Then, they are to be applied only in the cases, where we cannot use a parametric test. In the paper, some examples of non-parametric tests will be discussed. There are following groups of non-parametric tests: