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New Measures of Skewness of a Probability Distribution
RGG Department, Harrah College of Hospitality, University of Nevada, Las Vegas, USA
Department of Computer Science, University of Nevada, Las Vegas, USA
Department of Computer Science, University of Nevada, Las Vegas, USA
- 1 RGG Department, Harrah College of Hospitality, University of Nevada, Las Vegas, USA
- 2 Department of Computer Science, University of Nevada, Las Vegas, USA
- 3 Department of Computer Science, University of Nevada, Las Vegas, USA
Open Journal of Statistics·Volume 09 (2019)·Pages 601–621·Published 5 September 2019·DOI10.4236/ojs.2019.95039
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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).
KeywordsSample MomentsQuantilesComputational GeometrySymmetryRobust MeasureCentral Limit TheoremTrapezoid Rule
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