 The statement \(\Pr(\neg H\pmid E) = 1-\Pr(H\pmid E)\) is a theorem of the probability calculus. If the probability of \(H\) given \(E\) is low, the probability of \(\neg H\) given the same evidence must be high. This fact may seem to create evidence from ignorance. If \(E\) is meager evidence of \(H\) (that is, \(\Pr(H \pmid E)\) is low), it must be strong evidence for the negation of \(H\) (that is, \(\Pr(\neg H \pmid E)\) is high). This seems wrong. Intuitively, some evidence can weakly support both a hypothesis and its negation. For example, suppose one has heard a rumor that the defendant spent the night at the bar when the crime was committed. The rumor is weak evidence for the claim that the defendant spent the night at the bar. It does not follow that the rumor is strong evidence that the defendant did not spend the night at the bar. Evidence may actually have no bearing whatsoever on a hypothesis. Probability seems unable to capture this fact, or at least this is the objection.