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Combined Tests for Comparing Mutabilities of Two Populations

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Topics in Statistical Simulation

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 114))

Abstract

Mutability is the aptitude of a qualitative variable to assume different categories [3]. With numerical variables, dispersion and heterogeneity of values, that is variability, may be measured by means of range, interquartile range, variance, standard deviation, coefficient of variation, mean absolute deviation, and several other indexes. With categorical data, in particular with nominal variables, the concept of mutability takes the place of that of variability. Mutability may be measured by other indexes mainly based on the observed frequencies: index of Gini [3], entropy of Shannon [6], family of indexes proposed by Rényi [5], and many others.

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References

  1. Arboretti Giancristofaro, R., Bonnini, S., Pesarin, F.: A permutation approach for testing heterogeneity in two-sample problems. Stat. Comput. 19, 209–216 (2009)

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  2. Bonnini, S.: Testing for heterogeneity with categorical data: permutation solution vs. bootstrap method. Commun. Stat.: Theory Methods 43(4), 906–917 (2014)

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  3. Gini, C.: Variability and mutability, contribution to the study of statistical distributions and relations. Studi Economico-Giuridici della R. Universita di Cagliari (1912)

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  4. Pesarin, F., Salmaso, L.: Permutation Tests for Complex Data. Theory, Applications and Software. Wiley, Chichester (2010)

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  5. Rényi, A.: Calculus des probabilitès. Dunod, Paris (2009)

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  6. Shannon, C.E.: A mathematical theory of communication. Syst. Technol. J. 27, 379–423 (1948)

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Correspondence to Stefano Bonnini .

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Bonnini, S. (2014). Combined Tests for Comparing Mutabilities of Two Populations. In: Melas, V., Mignani, S., Monari, P., Salmaso, L. (eds) Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2104-1_7

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