To a Bayesian, evidence is a quantitative concept. In principle, a hypothetical Bayesian superintelligence could say not only *that* the evidence supports a particular hypothesis, but by *how much*. (In practice the true math is usually intractable.) The more complicated or *a priori* improbable a hypothesis is, the more evidence you need just to justify it, or even just single it out of the amongst the mass of competing theories.

We often find it convenient to express the **amount of evidence** in terms of logarithms of odds, *decibels* if we use the base-10 logarithm, *bits* if we use the base-2.

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