ESE 306 Study Guide - Midterm Guide: Probability Mass Function, Random Variable, Cumulative Distribution Function

• School: Stony Brook University
• Department: Electrical Engineering
• Course: ESE 306
• Professor: Ji Liu

Document Summary

Laws of probability: the set of all possible outcomes of an experiment is known as sample space, and it is denoted by . It is given by (cid:18)n k(cid:19) = n! k! (n k)! Geometric series: the sum of the rst n + 1 terms of a geometric. P (a b) = p (a) + p (b) p (a b). series is given by: the probability of the intersection of two events. P (a b) is also denoted by p (a, b): the conditional probability of an event a given the occurrence of another event b is de ned by. 1 r r 6= 1: for n , the sum is given by. One random variable: total probability theorem: let b1, b2 . Bn be a partition of the sample space , that is (a) b1 b2 . Bn = and (b) bi bj = i 6= j.