STAT151 Lecture Notes - Lecture 17: Bernoulli Trial, Probability Distribution, Random Variable

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Omar Rivasplata

Document Summary

A random variable assumes a value based on the outcome of a random event: we use a capital leter, like x, to denote a random variable o. A paricular value of a random variable will be denoted with a lower case leter, in this case x. There are two types of random variables: o o. Discrete random variables can take one of a inite number of disinct outcomes. Coninuous random variables can take any numeric value within a range of values. A probability model or probability distribuion for a random variable consists of: o o. The collecion of all possible values of a random variable, and the probabiliies that the values occur. Of paricular interest is the value we expect a random variable to take on, notated (for populaion mean) or e(x) for expected value. The expected value of a (discrete) random variable can be found by summing the products of each possible value and the probability that it occurs: