EC255 Lecture Notes - Lecture 5: Collectively Exhaustive Events, Weighted Arithmetic Mean, Negative Probability
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Ec255 lecture #5: bayes" rule & discrete distributions. Learning objectives: bayes" rule, probability (decision) tree approach table approach. Conditional probability: conditional probability for events e1 and e2: (cid:4666)(cid:2869)|(cid:2870)(cid:4667)=(cid:4666)(cid:3117) (cid:3118)(cid:4667) (cid:4666)(cid:3118)(cid:4667) the ratio of the relative size of e1 e2 to e2 is p(e1 | e2) A variety of prep courses are designed to help improve gmat scores (200-800). An applicant has determined that he needs 650 to get into an mba program, but he feels that his probability of getting 650 is 10%. Suppose a survey reveals that among gmat scorers of 650, 52% took a prep course, whereas among scorers of < 650, only. He is considering taking a prep course that cost , but is only willing to do so if his probability of achieving 650 doubles. Learning objectives: distinguish between discrete random variables and continuous random variables, compute mean and variance of a discrete distribution, understand the binomial distribution and its applications.
