2026-07-072026-07-07http://salesiana.dossiersoluciones.com/handle/123456789/117956We derive sufficient conditions for a family $(X^n,ρ_n,P_n)$ of metric probability spaces to have the measure concentration property. Specifically, if the sequence $\{P_n\}$ of probability measures satisfies a strong mixing condition (which we call $η$-mixing) and the sequence of metrics $\{ρ_n\}$ is what we call $Ψ$-dominated, we show that $(X^n,ρ_n,P_n)$ is a normal Levy family. We establish these properties for some metric probability spaces, including the possibly novel $X=[0,1]$, $ρ_n=\ell_1$ case.Keywords: concentration of measure, martingale differences, metric probability space, Levy family, strong mixingProbabilityFunctional Analysis60A99; 60G42text