  What is the relationship between plausibility logic and the principle of
maximum entropy? When does the principle give unreasonable or wrong results?
When is it appropriate to use the rule `expectation = average'? Can
plausibility logic give the same answers as the principle, and better answers
if those of the principle are unreasonable? To try to answer these questions,
this study offers a numerical collection of plausibility distributions given by
the maximum-entropy principle and by plausibility logic for a set of fifteen
simple problems: throwing dice.
