In measuring, testing, and experimenting, statistical tests are made to determine whether the observed effect of the introduction of a factor is real or simply due to chance. The appropriate statistical test to use depends on the kind of distribution used to model the data. Distribution identification is useful in selecting the most powerful statistical test.
Note 2—There are statistical tests which can be used for data for which a parametric distribution cannot be selected. But these non-parametric tests do not discriminate as well as the distribution-dependent tests.
For certain types of data, a transformation can be made which will make it possible to use the hypothesis that the normal distribution is a suitable model for the transformed data. When this hypothesis can be made, the analysis of the data is made much easier.