Dave and others,
- Moving right along -- hopefully, the rest of my premises:
11. To formally re-evaluate OOFLam, we can use the following formula from Bayesian statistics: P(H|E)=P(E|H)*P(H)/(P(E|H)*P(H)+P(E|~H)*P(~H)).
12. There are 3 variables in that formula -- we've already discussed P(E|H), the likelihood of the event occurring, given H (OOFLam).
13. Another variable is the prior probability of H (and ~H).
14. There is a reasonable probability of at least 1% for ~H -- and therefore, no more than 99% for H.
15. The remaining variable is P(E|~H), the likelihood of the event occurring, given ~H. For now, I'll suggest 99%.
16. Inserting the numbers, we get that the posterior probability of H, after adding E to the evidence is: P(H|E)=10-100*.99/(10-100*.99+.99*.01). And rounding off, we get P(H|E)=0/.099, or zero.
17. So, by adding this new info to the evidence for H and rounding off, we get that the probability of H being true is zero.
- That ought to give us some more disagreements to discuss.