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Priors are Useless.
Priors are irrelevant. Given two different prior probabilities Pri1, and Pri2 for some hypothesis Hi. Let their respective posterior probabilities be Priz1 and
. After sufficient number of experiments, the posterior probability
. Or More formally: limn→∞Priz1Priz2=1. Where n is the number of experiments. Therefore, priors are useless. The above is true, because as we carry out subsequent experiments, the posterior probability Priz1j gets closer and closer to the true probability of the hypothesis Pri. The same holds true for Priz2j. As such, if you have access to a sufficient number of experiments the initial prior hypothesis you assigned the experiment is irrelevant.
In the example above, the true probability of Hypothesis Hi(Pi) is 0.5 and as we see, after sufficient number of trials, the different Priz1js get closer to 0.5.
To generalize from my above argument:
If you have enough information, your initial beliefs are irrelevant—you will arrive at the same final beliefs.
Because I can’t resist, a corollary to Aumann’s agreement theorem. Given sufficient information, two rationalists will always arrive at the same final beliefs irrespective of their initial beliefs.
The above can be generalized to what I call the “Universal Agreement Theorem”:
Given sufficient evidence, all rationalists will arrive at the same set of beliefs regarding a phenomenon irrespective of their initial set of beliefs regarding said phenomenon.
Priors Are Useless
NOTE.
This post contains Latex. Please install Tex the World for Chromium or other similar Tex typesetting extensions to view this post properly.
Priors are Useless.
Priors are irrelevant. Given two different prior probabilities Pri1, and Pri2 for some hypothesis Hi.
Let their respective posterior probabilities be Priz1 and
After sufficient number of experiments, the posterior probability
Or More formally:
limn→∞Priz1Priz2=1.
Where n is the number of experiments.
Therefore, priors are useless.
The above is true, because as we carry out subsequent experiments, the posterior probability Priz1j gets closer and closer to the true probability of the hypothesis Pri. The same holds true for Priz2j. As such, if you have access to a sufficient number of experiments the initial prior hypothesis you assigned the experiment is irrelevant.
To demonstrate.
http://i.prntscr.com/hj56iDxlQSW2x9Jpt4Sxhg.png
This is the graph of the above table:
http://i.prntscr.com/pcXHKqDAS\_C2aInqzqblnA.png
In the example above, the true probability of Hypothesis Hi (Pi) is 0.5 and as we see, after sufficient number of trials, the different Priz1js get closer to 0.5.
To generalize from my above argument:
The above can be generalized to what I call the “Universal Agreement Theorem”:
Exercise For the Reader
Prove limn→∞Priz1Priz2=1.