Performances of Several Univariate Tests of Normality: An Empirical Study
Adefisoye JO, Golam Kibria BM* and George F
Department of Mathematics and Statistics, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA
- *Corresponding Author:
- Golam Kibria BM
Department of Mathematics and Statistics
Florida International University
11200 SW 8th Street, Miami, FL 33199, USA
Tel: +1 305-348-2000
E-mail: [email protected]
Received Date: September 23, 2016; Accepted Date: November 08, 2016; Published Date: November 11, 2016
Citation: Adefisoye JO, Golam Kibria BM, George F (2016) Performances of Several Univariate Tests of Normality: An Empirical Study. J Biom Biostat 7: 322. doi:10.4172/2155-6180.1000322
Copyright: © 2016 Adefisoye JO, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The problem of testing for normality is fundamental in both theoretical and empirical statistical research. This paper compares the performances of eighteen normality tests available in literature. Since a theoretical comparison is not possible, MonteCarlo simulation were done from various symmetric and asymmetric distributions for different sample sizes ranging from 10 to 1000. The performance of the test statistics are compared based on empirical Type I error rate and power of the test. The simulations results show that the Kurtosis Test is the most powerful for symmetric data and Shapiro Wilk test is the most powerful for asymmetric data.