| Npstat | NPSTAT and NPFACT are a subset of programs developed to carry out computer intensive analysis (such as randomization tests but not bootstrapping). They provide nonparametric methods of null hypothesis testing.
The null distribution consists of an empirical distribution based on the data at hand, which may be any shape, rather than a theoretical distribution generated by analytical methods (typically normal or known relation to normal, such as z, t, and F). The statistical tests are nonparametric in that they a) do not require interval or ratio scale of measurement, b) do not assume the data are randomly sampled from any a specific population, and c) do not require that the sample data, the population from which the data are taken, or the null distribution of the test statistic, have any particular shape. More traditional approaches to statistical testing may be found if you click here.
Variations of these tests most familiar to researchers include the Wilcoxon-Mann- Whitney test on ranks and Fisher's exact probability test for dichotomous data in a 2 X 2 contingency table. Major advances in computing in the last 15 years have allowed these nonparametric procedures to be adapted to a greater variety of research applications involving scores in one-way and factorial designs, multiple regression, and multivariate analysis.
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