rocketdodger
Philosopher
- Joined
- Jun 22, 2005
- Messages
- 6,946
Okay, second try, doing the math correctly this time. Let's start with a simple definition of conditional probability :
P(E) = P(E|H)P(H) + P(E|-H)P(H).
We now assume that I have access to an event generator that will generate events independent of E with probability 0.5. This is not a big assumption, since I have access to a whole jar-full of them; they're called coins. H is therefore just an event "I flipped heads," and P(H) = P (-H) = 0.5.
Furthermore, since this event is by construction independent of E, P(E|H) = P(E) and P(E|H)P(H) = P(E)/2 = P(E|H)/2.
Similarly, P(E|-H) = P(E) and P(E|-H)P(-H) = P(E)/2 = P(E|-H)/2.
And since P(E|H)/2 = P(E)/2 = P(E|-H)/2, we have that P(E) = P(E|H) = P(E|-H).
Your claim is that, in the absence of any other information about P(E), we should assume that P(E|H) + P(E|-H) = 1.
But, mathematically, this works out to be that P(E|H) + P(E|H) = 1.0, which in turn means that P(E|H) = 0.5, which in turn means that P(E) = 0.5
So your suggested constraint ends up being much stronger than the claim you rejected, namely that we cannot estimate P(E). We have. If I have no information on it whatsoever, then P(E) must be equal to 0.5.
So you end up either supporting Malerin's formulation --- the a priori probability of God existing is 0.5, or you end up needing to reject your own overconstraint.
Well, three things:
First, this the result I intended, and I think the math in my OP agrees with what you did -- if P(H) is 0.5, then P(E) must be 0.5 as well.
Second, this is not analagous to Malerin's example! He uses H = a universe creator and E = a life supporting universe. That means E is not independent of H -- specifically, he is assuming a value very close to unity for P(E|H) because the fine-tuning argument relies on a high probability of a life supporting universe given that a universe creator exists.
That is why I could not use the equivalences you did I.E. P(E) = P(E|H) and P(E) = P(E|~H). P(E) is definitely not equal to P(E|H) in the fine tuning argument.
Third, is arriving at a value for P(E) (assuming E is not independent of H) using the conditional probabilities P(E|H) and P(E|~H) still considered "a priori?"
Because my contention was that a valid use of Bayes Theorem requires a true a priori estimate for both priors, that in this case we can't get a good a priori estimate, that instead we must rely on the above relationship between the unconditional and the conditionals to get any value of P(E) in order to use Bayes at all nevermind properly, and since we rely on the conditionals all bets are off when it comes to interpreting the results -- illustrated by my claim that P(E) is dependent on P(H) when one expect it should not be for a proper analysis.
Do you still think this is wrong?