Exercise: You will win if both a fair coin lands heads AND a fair die lands 6. After the coin is flipped and the die is rolled you ask if at least one of these events has occurred and you are told "yes."
One of the question is about specifying and calculating the posterior distribution for the joint probability of the coin and dice events given the event that the coin is heads or dice is six, ?(?,?|? = ????).
Using Bayes theorem, this is what I have managed to achieve so far:
I don't know what value the likelihood should be. Also, I would like to know if im following the correct approach?
Thank you in advance.
One of the question is about specifying and calculating the posterior distribution for the joint probability of the coin and dice events given the event that the coin is heads or dice is six, ?(?,?|? = ????).
Using Bayes theorem, this is what I have managed to achieve so far:
- p(heads and six) = 1/12 or (0.083)
- p(heads or six) = 7/12 or (0.583)
- P(R=True): Prior probability
- P(C, D): Evidence
- P(? = ????| ?,?): Likelihood
- P(?,?|? = ????): Posterior probability
I don't know what value the likelihood should be. Also, I would like to know if im following the correct approach?
Thank you in advance.