ELEG 3143 Lecture Notes - Lecture 6: Bernoulli Distribution, Probability Mass Function, Random Variable

• School: University of Arkansas
• Department: Electrical Engineering
• Course: ELEG 3143
• Professor: Robert Saunders

Document Summary

Lec 6 continuing definitions, probability mass functions (pmf), families of discrete random variables. Student can earn b or c from two different courses. B is worth 3 points, c is worth 2. Gpa (g) is the sum of the points earned for each course divided by 2. Make table of sample space & corresponding values of gpa. Function that gives the probability that a discrete random variable is exactly equal to some value. The pmf of random variable x expresses the probability model of an experiment as a mathematical function. The function is the probability p[x=x] for every number x. Probability mass function (pmf) of the discrete random variable x is. For a discrete random variable x with pmf and range. For any event the probability that x is in the set. In applications of probability, many experiments have similar probability mass functions.