marginal-likelihood-constant-across-hypotheses

Summary

When comparing competing explanations for the same evidence, the overall probability of observing that evidence is fixed regardless of which explanation you are evaluating, so it drops out of the comparison entirely. This is what makes Bayesian model comparison practical: you only need to compute the much simpler likelihood terms for each hypothesis, not the notoriously difficult normalizing constant that would otherwise be required.