where mX and mY are the observed sample means, nX and nY are the sample sizes of the two groups, and s is an estimate of the common standard deviation. If the assumptions are violated, T is compared with the wrong reference distribution, which may result in a deviation of the actual Type I error from the nominal significance level [12,13], in a loss of power relative to other tests developed for similar problems [14], or both. In medical research, normally distributed data are the exception rather than the rule [15,16]. In such situations, the use of parametric methods is discouraged, and nonparametric tests (which are also referred to as distribution-free tests) such as the two-sample Mann–Whitney U test are recommended instead [11,17].