EVALUATION OF SENSITIVITY OF THREE SELECTED TWO- SAMPLE NONPARAMETRIC TESTS

Abstract

In this paper, comparison of two sample tests, is motivated by the fact that in the test of significant difference
between two independent samples, numerous methods can be adopted, each may lead to significant different
results; this implies that wrong choice of test statistic could lead to erroneous conclusion. To prevent misleading
information, there is a need for proper investigation of some selected methods for test of significant difference
between variables/subjects most especially, independent samples. In this paper, Monte Carlo’s Simulation
techniques were used in the generation of data of two different distributions and varying sample sizes ranging
from 5 to 100 which were repeated 30 times for each sample size. In the simulation, sample sizes 5, 10, 20, 30,
50 and 100 were considered. In the paper, data from a known family of distributions; Gamma (4, 0.3) and
Weibull (7, 3) were used. This paper examines the sensitivity/efficiency of Mann-Whitney U test, Modified
Mann-Whitney U test and Kolmogorov-Smirnov two-sample test to determine the most powerful test in terms of
rejecting the null hypothesis when it is true. From the results, Mann-Whitney U-test was found to be the most
powerful test in terms of rejecting the null hypothesis when it is true.