New Measures of Skewness of a Probability Distribution

作     者：Ashok K. Singh Laxmi P. Gewali Jiwan Khatiwada 

作者机构：RGG Department Harrah College of Hospitality University of Nevada Las Vegas USA Department of Computer Science University of Nevada Las Vegas USA 

出 版 物：《Open Journal of Statistics》 (统计学期刊（英文）)

年 卷 期：2019年第9卷第5期

页      面：601-621页

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

主　　题：Sample Moments Quantiles Computational Geometry Symmetry Robust Measure Central Limit Theorem Trapezoid Rule 

摘      要：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).