Uses Monte Carlo methods to assess the relative power of the paired samples t test and Wilcoxon's signed-ranks test under 10 population shapes. Concludes that, insofar as these two statistics are concerned, the often-repeated claim that parametric tests are more powerful than nonparametric tests is not justified. (Author/CB)

The author contends Glass, Peckham, and Sanders erred in discouraging the use of nonparametric counterparts of the t-test, even when it was known data were sampled from skewed distributions. He believes Wilcoxon's rank-sum test has power properties that make it preferable in most nonnormal population situations. (Author/DWH)

Monte Carlo techniques were used to compare the power of Wilcoxon's rank-sum test to the power of the two independent means t test for situations in which samples were drawn from (1) uniform, (2) Laplace, (3) half-normal, (4) exponential, (5) mixed-normal, and (6) mixed-uniform distributions. (Author/JKS)

Monte Carlo methods were employed to assess the relative power of the paired samples t test and Wilcoxon's signed-ranks test under ten population shapes. Results of the study indicated that: (1) each of the two statistics was more powerful than the other in given situations; (2) the power advantages of the t test under normal theory were small;…