In this paper, we draw attention to a promising yet slightly underestimated measure of variability - the Gini coefficient. We describe two new ways of defining and interpreting this parameter. Using our new representations, we compute the Gini index for a few probability distributions and describe it in more detail for the negative binomial distribution. We also suggest the latter as a tool to measure overdispersion in epidemiology.

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Milewska, M, van der Hofstad, R.W, & Zwart, A.P. (2022). Two more ways of spelling Gini Coefficient with Applications. doi:10.48550/arXiv.2201.12298