Basic Statistical Tests

Abstract

Two main groups of statistical tests are parametric and nonparametric tests (Good, 2005). Parametric tests assume that the underlying data are normally distributed and nonparametric tests start off with the assumption that the underlying data do not have a normal distribution (Adler, 2012). Assuming that data are normally distributed is usually correct (Adler, 2012), and therefore parametric tests are more commonly applied than nonparametric ones. Nonparametric tests are also referred to as distribution-free tests, and they can be particularly useful when the data are measured on a categorical scale, i.e., when we deal with an ordered data set (Petrie and Sabin, 2005). It should be noted that nonparametric tests are less powerful in comparison to equivalent parametric tests (Vuković, 1997).