Can I Predict the Correct Dice Using Probability Distributions?

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The discussion revolves around predicting which die was rolled based on their differing probability distributions after observing a result, x. The best strategy is to choose the die with the higher probability of rolling x. The probability of correctly identifying the die is influenced by the values of pA(x) and pB(x), with specific cases leading to 100% or 50% certainty. Bayesian inference is suggested as a method to calculate the probability of the die being A or B after rolling. The application of Bayes' theorem is confirmed as a suitable approach for this problem.
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Say I have two dice which have different probability distributions but I don't know which probability distribution belongs to what dice.
I now throw one of them exactly one time and the result is x. I know that die A has probability pA(x) for rolling x and die B has probability pB(x).
I want to find out if the die I rolled was die A or B. Obviously my best strategy is to guess the die for which the probability for rolling x is the bigger. But what is my probability for being correct? I have been trying to figure out this problem for days. Obviously if pB(x)=0 while pA(x)>0 I have 100% chance of being correct. Moreover if pB(x)=pA(x) then I have 50% chance of being correct. But is there an expression for arbitrary probabilities and how do I find it?
 
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Nice question. This would be a perfect application for Bayesian inference.

Are you familiar with Bayes theorem?
 
Yes P(XlY) = P(YlX) * P(Y)/P(X)

So in my case P(Alx) is the probability that the die is A given that it shows x, while P(xlA) is the probability that the die shows x given that it is die A and P(A) is the probability that it is die A given no prior information, i.e. P(A)=0.5 and P(x) is then the probability for tossing an x given no prior information, which would be 0.5*(pA(x)+pB(x)).. hmm.. is that correct?
 
Yes. I think that is correct.
 
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