Question: Suppose that we have 2 fair coins, coin A and coin B. If we obtained 2 heads after 2 tosses, what is the probability that the coin is A?
My attempt:
By the Bayes' Theorem, we have $$P(A|HH) = \frac{P(HH|A)\times P(A)}{P(HH|A)\times P(A) + P(HH|B)\times P(B)}$$
Here is my question.
I know that $P(HH|A)$ can be calculated by calculating $[P(H|A)]^2.$ But how to prove they are the same rigirously?
From definition of conditional probability, we should have $$P(HH|A) = \frac{P(HH\cap A)}{P(A)}.$$ But the numerator does not make sense to me as both $HH$ and $A$ come from different sample space.
If you have two fair coins, then they are indistinguishable. The probability that the coins is A is $1/2$. No need for any long reasoning.
If you need to answer the second question. The coins are fair, the event A give you no information (the events H and A are independent) hence $$P(HH\mid A)=\frac{P(HH\cap A)}{P(A)}=\frac{P(HH)P(A)}{P(A)}=P(HH)$$ By independence of event $$P(HH\mid A)=P(HH)=P(H)^2$$ And using the first argument again $$P(HH\mid A)=P(HH)=P(H)^2=P(H\mid A)^2$$