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We consider Gini's mean difference statistic as an alternative to theempirical variance in the settings of finite populations where simple randomsamples are drawn without replacement. In particular, we discuss specific (inthe finite population context) estimation strategies for a scale of thepopulation, related to the alternative statistic under possible presence ofoutliers in the data. The paper presents also a wide comparative survey ofproperties of the Gini mean difference statistic and the empirical variance. Itincludes asymptotic properties of both statistics: the asymptotic normality,one-term Edgeworth expansions and bootstrap approximations for Studentizedversions of the statistics. An estimation of the variances and other parametersof the statistics is also in the study, where we exploit an auxiliaryinformation on the population elements in the case of its availability.Theoretical results are illustrated with a simulation study.

Gini's mean difference and variance as measures of finite populations scales