Human behavior in many situations involving uncertainty and risk depends on the acquisition of information concerning event probabilities. A family of statistical models, growing out of general mathematical learning theory, accounts for probability learning in terms of the accumulation in memory of weighted ensembles of associations between recurring situations and subsequent events. These models provide rather detailed quantitative accounts of probability learning in some especially simplified experimental situations. Also they provide vehicles for applying theoretical interpretations of probability learning to the problems of choice and decision making in social and economic contexts.