 (As an aside, it should be noticed that, according to standard Bayesian usage, the term “priors” does not necessarily refer to the degrees of belief a person assigns before the receipt of any data. If there are already data in, then, clearly, one may assign higher priors to hypotheses that best explain the then-available data. However, one can sensibly speak of “best explanations” even before any data are known. For example, one hypothesis may be judged to be a better explanation than any of its rivals because the former requires less complicated mathematics, or because it is stated in terms of familiar concepts only, which is not true of the others. More generally, such judgments may be based on what Kosso (1992, 30) calls internal features of hypotheses or theories, that is, features that “can be evaluated without having to observe the world.”)