P(H)=P(H,E)+P(H,¬E) =P(H|E)⋅P(E)+P(H|¬E)⋅P(¬E)

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.

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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:~~is

*D*_{1} = *P*(*H*|*E*) − *P*(*H*).

If the evidence is negative, the change ~~is:~~is

~~\(D_{2}~~*D*_{2} = ~~P(H|\neg{E}~~*P*(*H*|¬*E*)~~-P(H)\\~~ − *P*(*H*).

*D*_{1} ⋅ *P*(*E*) = − *D*_{2} ⋅ *P*(¬*E*).

**Conservation of Expected Evidence **is a consequence of probability theory which states that for every expectation of evidence, there is an equal and opposite expectation of ~~counterevidence.~~counterevidence [1]. Conservation of Expected Evidence is about ~~bot~~both the direction of the ~~update,~~update and its ~~magnitude -~~magnitude: 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[~~direction [2]. The mere *expectation *of encountering evidence–before you've actually seen it–should not shift your prior beliefs. It also goes by other names, including *the **law of total expectation* and *the law of iterated expectations*.

Yoav Ravid v1.8.0Nov 20th 2021 (+8/-8) added link to "absence of evidence is evidence of absence" LW2

A consequence of this principle is that absence of evidence is evidence of ~~absence.~~absence.

Yoav Ravid v1.7.0Nov 20th 2021 (+257/-177) Added a sentence to the start clarifying that conservation of expected evidence takes both magnitude and direction into account LW2

**Conservation of Expected Evidence **is a consequence of probability theory which states that for every expectation of evidence, there is an equal and opposite expectation of counterevidence. [1] Conservation of Expected Evidence is about bot the direction of the update, and its magnitude - 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[2]. The mere *expectation *of encountering evidence–before you've actually seen it–should not shift your prior beliefs. It also goes by other names, including *the **law of total expectation* and *the law of iterated expectations*.

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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**Conservation of Expected Evidence **is a consequence of probability theory which states that for every expectation of evidence, there is an equal and opposite expectation of counterevidence. [1] The mere *expectation *of encountering evidence–before you've actually seen it–should not shift your prior beliefs. It also goes by other names, including *the **law of total expectation* and *the law of iterated expectations*.

~~From ~~~~Conservation of Expected Evidence~~~~:~~

~~If you expect a strong probability of seeing weak evidence in one direction, it must be balanced by a weak expectation of seeing strong evidence in the other direction. If you’re very confident in your theory, and therefore anticipate seeing an outcome that matches your hypothesis, this can only provide a very small increment to your belief (it is already close to 1); but the unexpected failure of your prediction would (and must) deal your confidence a huge blow. On~~~~average~~~~, you must expect to be~~~~exactly~~~~as confident as when you started out. Equivalently, the mere~~~~expectation~~~~of encountering evidence—before you’ve actually seen it—should not shift your prior beliefs.If you expect a strong probability of seeing weak evidence in one direction, it must be balanced by a weak expectation of seeing strong evidence in the other direction. If you’re very confident in your theory, and therefore anticipate seeing an outcome that matches your hypothesis, this can only provide a very small increment to your belief (it is already close to 1); but the unexpected failure of your prediction would (and must) deal your confidence a huge blow. On~~~~average~~~~, you must expect to be~~~~exactly~~~~as confident as when you started out. Equivalently, the mere~~~~expectation~~~~of encountering evidence—before you’ve actually seen it—should not shift your prior beliefs.~~

~~These principles~~Consider a hypothesis H and evidence (observation) E. Priorprobability 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:

*P*(*H*|*E*) ⋅ *P*(*E*) + *P*(*H*|¬*E*) ⋅ *P*(¬*E*)

But the prior probability of the hypothesis itself can be ~~proven within standard~~trivially broken up the same way:

P(H)=P(H,E)+P(H,¬E)=P(H|E)⋅P(E)+P(H|¬E)⋅P(¬E)

Thus, expectation of posterior probability ~~theory. From ~~~~Absence of Evidence ~~is ~~Evidence of Absence~~~~:~~equal to the prior probability.

~~But in probability theory, absence of~~~~evidence~~~~is always~~~~evidence~~~~of absence. If E is a binary event and P(H | E) > P(H), i.e., seeing E increases~~In other way, if you expect the probability of~~H,~~a hypothesis to change as a result of observing some evidence, the amount of this change if the evidence is positive is:

D_{1}=P(H|E) −P(H)If the evidence is negative, the change is:

\(D_{2} = P(H|\neg{E})-P(H)\\)

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

D_{1}⋅P(E) = −D_{2}⋅P(¬E)If you can

anticipate in advanceupdating your belief in a particular direction, then~~P(H | ¬ E) < P(H), i.e., failure to observe E decreases the~~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~~H . The~~seeing strong evidence in one direction must be balanced by a high probability~~P(H) is a weighted mix~~of~~P(H | E) and P(H | ¬ E), and necessarily lies between~~observing weak counterevidence in the~~two.~~other direction.## Notable Posts

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~~Tag Status: C-Class~~

*Tag Status: C-Class*

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Conservation of Expected Evidenceis a consequence of probability theory which states that for every expectation of evidence, there is an equal and opposite expectation of~~counterevidence~~counter-evidence [1]. Conservation of Expected Evidence is about both the direction of the update and its magnitude: a low probability of seeing strong evidence in one direction must be balanced by a high probability of observing weak~~counterevidence~~counter-evidence in the other direction [2]. The mereof encountering evidence–before you've actually seen it–should not shift your prior beliefs. It also goes by other names, includingexpectationtheandlaw of total expectation.the law of iterated expectationsConsider 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)~~counter-evidence). 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:P(H|E)⋅P(E)+P(H|¬E)⋅P(¬E)P(H)=P(H,E)+P(H,¬E)=P(H|E)⋅P(E)+P(H|¬E)⋅P(¬E)

D_{1}=P(H|E)−P(H)~~.~~D_{2}=P(H|¬E)−P(H)~~.~~Expectation of the change given positive evidence is equal to negated expectation of the change given

~~counterevidence:~~counter-evidence:D_{1}⋅P(E)=−D_{2}⋅P(¬E)~~.~~