New Measures of Skewness of a Probability Distribution

• 作者: Ashok K. Singh Jiwan Khatiwada Laxmi P. Gewali
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: Sample MOMENTS QUANTILES Computational Geometry SYMMETRY Robust Measure Central Limit Theorem TRAPEZOID Rule
• 年，卷（期）: 2019,（5）
• 页码范围: 601-621
• 页数: 21页
• 分类号: O17

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).