Bayes' theorem
Prior odds:
- O(H) = P(H) / P(¬H) = P(H) / (1 - P(H))
Likelihood ratio:
- L(e | H) = P(e | H) / P(e | ¬H)
Posterior odds:
- O(H | e) = P(H | e) / P(¬H | e) = L(e | H)O(H)
Posterior probability:
- P(H | e) = P(e | H)P(H) / P(e)
= O(H | e) / (1 + O(H | e))