STAT 1053 Lecture Notes - Lecture 5: Fair Coin, Continuous Or Discrete Variable, Fluid Ounce
Document Summary
Events a and b are independent events if the occurrence of b does not alter the probability that a has occurred (that a occurs); i. e. , a and b are independent if. When events a and b are independent, it is also true that p(b|a) = Events that are not independent are said to be dependent. If events a and b are independent, the probability of the intersection of a and b equals the product of the probabilities of a and b, i. e. , The converse is also true: if p(a b)= p(a) p(b) holds, the events. Conditional probability, the multiplicative rule, and independence are in sections 3. 5 and 3. 6, but ignore tree diagrams , pp. Suppose a student is selected at random from the population of undergraduates at a college. A: the event that the student is majoring in the arts/sciences, L: the event that the student is local. You are given p(a)= 0. 30, p(a l)= 0. 18, p(l)=0. 60.
