4-E4. We are trying to decide whether to release a new TV program which is at the pilot stage. Our prior distribution for the three possible outcomes is that 9% are monsters, 17% hits and 74% flops. We are going to do some market testing. To give an idea of the accuracy of the market testing, you are told the following set of conditional probabilities:
Pr(+|Monster) 0.889 Pr(+|Hit) 0.706 Pr(+|Flop) 0.419
A programme is market tested and received a positive assessment. Use Bayes method to obtain the posterior distribution. What is the chance of a programme being positively assessed?
P(+) = P(+ | monster) * P(monster) + P(+ | hit) * P(hit) + P(+ | flop) * P(flop)
= 0.889 * 0.09 + 0.706 * 0.17 + 0.419 * 0.74
= 0.51009
= 0.51
4-E4. We are trying to decide whether to release a new TV program which is at the pilot stage. Our prior distribution for the three possible outcomes is that 9% are monsters, 17% hits and 74% flops. W...