New Measures of Skewness of a Probability Distribution - Open Journal of Statistics

OJS > Vol.9 No.5, October 2019

Open Journal of Statistics

Volume 9, Issue 5 (October 2019)

ISSN Print: 2161-718X ISSN Online: 2161-7198

Google-based Impact Factor: 1.45 Citations

New Measures of Skewness of a Probability Distribution ()

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Download as PDF (Size: 8603KB) PP. 601-621

DOI: 10.4236/ojs.2019.95039 1,609 Downloads 5,306 Views Citations

Author(s)

Ashok K. Singh¹, Laxmi P. Gewali², Jiwan Khatiwada²

Affiliation(s)

¹RGG Department, Harrah College of Hospitality, University of Nevada, Las Vegas, USA.
²Department of Computer Science, University of Nevada, Las Vegas, USA.

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).

KEYWORDS

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

Share and Cite:

Singh, A. , Gewali, L. and Khatiwada, J. (2019) New Measures of Skewness of a Probability Distribution. Open Journal of Statistics, 9, 601-621. doi: 10.4236/ojs.2019.95039.

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