COMPSCI 240 Lecture Notes - Lecture 4: Bayes Estimator, Fair Coin, Conditional Independence
4 Dec 2018
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[ let ai , az , i. partition. Pladplbiad t putz ) plbi ah t unit plan ) plbi an ) Bayes " rule is often used for inference . what are the causes of the observations that. An a. causes: a- having disease or not. We are primarily interested in finding out the most likely. Question = suppose you roll two fair tour sided did than. Are a and aceh dependent it 0 < Plaabad = pla ) pl b) plc ) Pair wise independence does not imply the independence of all events. Suppose we have a finite collection of events ai , a2 , in. These events are said to be independent it. Esp lai ) , for every subset of s of } Probability of de mere losing [ having ae for all. B are conditionally independent given c ht :
