 We will illustrate the main ideas with a classic simple example, observing coin flips, and indicate how they can be generalized to more complex hypotheses. For more details please see [Genin and Kelly 2017, Genin 2018]. Suppose that an investigator has a question about the unknown bias \(p\) of a coin, where \(p\) represents the chance that a single flip comes out “Heads”. Different possible hypotheses correspond to different ranges of the bias \(p\), that is, a partition of [0,1], the range of the bias. Let us say that the investigator asks a simple point hypothesis: is the coin fair? Then we have