Industrial Engineering, Sharif University of Technology
School of Mathematical and Geospatial Sciences, RMIT University
Statistical analysis of non-normal data is usually more complicated than that for normaldistribution. In this paper, a simple root/power transformation technique developed by Niaki, et al is extended to transform right and left skewed distributions to nearly normal. The value of theroot/power is explored such that the skewness of the transformed data becomes almost zero with anacceptable error. The proposed method is then compared to the well-known and complicated Box, etal  transformation method for different left and right skewed distributions using Monte Carlosimulation. While the proposed procedure is easy to understand and to implement, the results of thesimulation study show that it works as good as the Box-Cox method.