JSM 2004 - Toronto

Abstract #301852

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Activity Number: 110
Type: Contributed
Date/Time: Monday, August 9, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #301852
Title: Evaluating Methods of Symmetry
Author(s): Jayawant N. Mandrekar*+ and Sumithra J. Mandrekar and Stephen S. Cha and Kent R. Bailey
Companies: Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic
Address: 200 First St. SW, Rochester, MN, 55905,
Keywords: distribution ; skewness ; symmetry
Abstract:

Skewness refers to the asymmetry in a distribution. The fundamental property of a symmetric distribution is that the corresponding upper and lower percentiles are equidistant from its median. Based on this underlying assumption, we propose an approach to identify the asymmetry in a continuous distribution using the absolute deviations below and above the median. We compare the performance characteristics of this new approach with several skewness measures and a non parametric test of symmetry using simulations. In conclusion, a graphical power law transformation by Hines and Hines (1987) to make a distribution symmetric will also be presented.

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