Nonparametric Test of Symmetry Using Overlapping Measures

Hani Samawi, Georgia Southern University
Amal Helu, Georgia Southern University
Robert L. Vogel, Georgia Southern University


In this paper, we introduce a new nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation. Our investigation reveals that the new test is more powerful than the runs test of symmetry proposed by McWilliams [31]. Intensive simulation is conducted to examine the power of the proposed test. Data from a level I Trauma center are used to illustrate the procedures developed in this paper.