STAB52H3 Lecture Notes - Lecture 7: Er1 Electric Trainset, Absolute Continuity, Probability Distribution
Document Summary
Definition 2. 8. 1 let x and y be random variables, and suppose that p(x. The conditional distribution of y, given that x = x, is the probability distribution assigning probability to each event y assigns probability. B, where b be a set of real numbers. In particular, it to the event that a < y b. Definition 2. 8. 2 let x and y be two discrete random variables. Then the conditional probability function of y, given x = x, is the function p y|x defined by defined for all y. R 1 and all x with px (x) > 0. Definition 2. 8. 5 let x and y be two random variables. Then x and y are independent if, for all subsets b1 and b2 of the real numbers, Theorem 2. 8. 2 let x and y be two random variables. Then x and y are independent if and only if whenever, a b and c d.
