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Brys, G., Hubert, M. and Struyf, A. (2003) A Comparison of Some New Measures of Skewness. In: Dutter, R., Filzmoser, P., Gather, U. and Rousseeuw, P.J., Eds., Developments in Robust Statistics, International Conference on Robust Statistics 2001, Physica-Verlag, Heidelberg, 98-113.
https://doi.org/10.1007/978-3-642-57338-5_8

has been cited by the following article:

• TITLE: New Measures of Skewness of a Probability Distribution

  AUTHORS: Ashok K. Singh, Laxmi P. Gewali, Jiwan Khatiwada

  KEYWORDS: Sample Moments, Quantiles, Computational Geometry, Symmetry, Robust Measure, Central Limit Theorem, Trapezoid Rule

  JOURNAL NAME: Open Journal of Statistics, Vol.9 No.5, October 31, 2019

  ABSTRACT: Symmetry of the underlying probability density plays an important role in statistical inference, since the sampling distribution of the sample mean for a given sample size is more likely to be approximately normal for a symmetric distribution than for an asymmetric one. In this article, two new measures of skewness are proposed and the confidence intervals for true skewness are obtained via Monte Carlo simulation experiments. One advantage of the two proposed skewness measures over the standard measures of skewness is that the proposed measures of skewness take values inside the range (-1, +1).