一种新的分组数据偏度系数

M. Eltehiwy, Abu-Bakr A. AbdulMotaal
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引用次数: 0

摘要

本文的主要目的是介绍一种新的检测分组数据偏度的方法,该方法在应用上比现有的方法更简单。新提出的偏度系数基于累积频率数据,因此使用了更多来自分布尾部的信息,因此将更适合于检测数据中的不对称性。新统计量的另一个优点是它的边界是-1和+1;因此,偏度系数可以很容易地解释。利用均方误差(MSE)和平均绝对误差(MAE)对文献中出现的三种经典偏度度量方法进行了仿真研究,以评估所提出的偏度系数的性能。仿真研究有力地支持使用所提出的度量来比较不同频率分布的偏度。
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A New coefficient of Skewness for grouped data
The primary objective of this paper is to introduce a new measure for detecting skewness for grouped data, which is simpler than the current measures in its application. The new proposed coefficient of skewness based on the cumulative frequency data and hence uses more information from the tails of the distribution and thus will be more appropriate to detect asymmetry in the data. Another advantage of the new statistic is that it is bounded by -1 and +1; hence, the coefficients of skewness can be interpreted easily. Simulation study is employed to assess the performance of the proposed coefficient of skewness with three of the classical measure of skewness appeared in the literature using the mean square error (MSE) and mean absolute error (MAE). The simulation study strongly supports the use of the proposed measure for comparing the degrees of skewness of different frequency distributions.
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