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Two simple measures of variability for categorical data

机译:两种简单的分类数据变异性度量

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This paper proposes two new variability measures for categorical data. The first variability measure is obtained as one minus the square root of the sum of the squares of the relative frequencies of the different categories. The second measure is obtained by standardizing the first measure. The measures proposed are functions of the variability measure proposed by Gini [Variabilita e Mutuabilita Contributo allo Studio delle Distribuzioni e delle Relazioni Statistiche, C. Cuppini, Bologna, 1912] and approximate the coefficient of nominal variation introduced by Kvalseth [Coefficients of variation for nominal and ordinal categorical data, Percept. Motor Skills 80 (1995), pp. 843-847] when the number of categories increases. Different mathematical properties of the proposed variability measures are studied and analyzed. Several examples illustrate how the variability measures can be interpreted and used in practice.
机译:本文提出了两种新的分类数据变异性度量。获得的第一可变性度量为一个减去不同类别相对频率平方和的平方根。通过将第一措施标准化来获得第二措施。拟议的措施是吉尼[Variabilita e Mutuabilita Contributo allo Studio delle Distribuzioni e delle Relazioni Statistiche,C. Cuppini,Bologna,1912]提出的可变性度量的函数,并近似由Kvalseth引入的名义变异系数[名义变异系数]和序数分类数据,感知。运动技能80(1995),第843-847页]。研究和分析了所提出的可变性测度的不同数学性质。几个示例说明了如何在实践中解释和使用可变性度量。

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