Urn models are the most versatile devices to represent chance processes, and they have a long and successful history in statistics. In 1780, the mathematician and philosopher Condorcet claimed that, “All questions in the Calculus of Probabilities can be reduced to a single hypothesis, that of a certain quantity of balls of different colors mixed together, from which different balls are drawn by hazard in a certain order or in certain proportions” (cited after Daston, 1988, p. 230). Condorcet would be pleased to know that today’s readers are guided through a wellwritten introductory statistics textbook with the help of a modified urn model, the box model (Freedman, et al., 1991). However, urn models are almost exclusively used by statistical experts (and those becoming statistical experts) and not by laypeople who struggle with solving statistical tasks in everyday life.