Difference between revisions of "Conservation of expected evidence"
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'''Conservation of expected evidence''' is a theorem that says: "for every expectation of evidence, there is an equal and opposite expectation of counterevidence". | '''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| | + | 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: |
| − | <math>P(H|E) \cdot P(E) + P(H|\ | + | <math>P(H|E) \cdot P(E) + P(H|\neg{E}) \cdot P(\neg{E})</math> |
But the prior probability of the hypothesis itself can be trivially broken up the same way: | But the prior probability of the hypothesis itself can be trivially broken up the same way: | ||
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<math>\begin{alignat}{2} | <math>\begin{alignat}{2} | ||
P(H) & = P(H) \\ | P(H) & = P(H) \\ | ||
| − | & = P(H,E) + P(H,\ | + | & = P(H,E) + P(H,\neg{E}) \\ |
| − | & = P(H|E) \cdot P(E) + P(H|\ | + | & = P(H|E) \cdot P(E) + P(H|\neg{E}) \cdot P(\neg{E}) |
\end{alignat}</math> | \end{alignat}</math> | ||
| Line 21: | Line 21: | ||
If the evidence is negative, the change is: | If the evidence is negative, the change is: | ||
| − | <math>D_{2} = P(H|\ | + | <math>D_{2} = P(H|\neg{E})-P(H)\ </math> |
Expectation of the change given positive evidence is equal to negated expectation of the change given counterevidence: | Expectation of the change given positive evidence is equal to negated expectation of the change given counterevidence: | ||
| − | <math>D_{1} \cdot P(E) = -D_{2} \cdot P(\ | + | <math>D_{1} \cdot P(E) = -D_{2} \cdot P(\neg{E})</math> |
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. | 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. | ||
Revision as of 07:44, 26 August 2010
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.
