Difference between revisions of "Conservation of expected evidence"

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<math>\begin{alignat}{2}
 
<math>\begin{alignat}{2}
P(H) & = P(H) \\
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P(H) & = P(H,E) + P(H,\neg{E}) \\
& = P(H,E) + P(H,\neg{E}) \\
 
 
& = P(H|E) \cdot P(E) + P(H|\neg{E}) \cdot P(\neg{E})
 
& = P(H|E) \cdot P(E) + P(H|\neg{E}) \cdot P(\neg{E})
 
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Revision as of 23:51, 19 March 2012

Conservation of expected evidence is a theorem that says: "for every expectation of evidence, there is an equal and opposite expectation of counterevidence".

Consider a hypothesis H and evidence (observation) E. Prior probability of the hypothesis is P(H); posterior probability is either P(H|E) or P(H|¬E), depending on whether you observe E or not-E (evidence or counterevidence). The probability of observing E is P(E), and probability of observing not-E is P(¬E). Thus, expected value of the posterior probability of the hypothesis is:

But the prior probability of the hypothesis itself can be trivially broken up the same way:

Thus, expectation of posterior probability is equal to the prior probability.

In other way, if you expect the probability of a hypothesis to change as a result of observing some evidence, the amount of this change if the evidence is positive is:

If the evidence is negative, the change is:

Expectation of the change given positive evidence is equal to negated expectation of the change given counterevidence:

If you can anticipate in advance updating your belief in a particular direction, then you should just go ahead and update now. Once you know your destination, you are already there. On pain of paradox, a low probability of seeing strong evidence in one direction must be balanced by a high probability of observing weak counterevidence in the other direction.

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See also