We explore how the classical Bhatia-Davis inequality bounding variances can be extended to uncertainty evaluations of gambles (bounded random numbers) by means of imprecise (lower or upper) previsions with different degrees of consistency. Firstly, a number of extensions are found with 2-coherent imprecise previsions. Subsequently, bounds with coherent lower and upper previsions are investigated, together with applications bounding lower and upper variances as well as p-boxes. Finally, bounds for covariances and for lower and upper covariances are obtained. Like the classical situation, imprecise Bhatia-Davis inequalities require a reduced amount of uncertainty information to be applied. When even less information is available, we show that various versions of Popoviciu's inequality obtain.
