STAT 2040 Lecture Notes - Lecture 5: Geometric Distribution, Probability Mass Function, Bernoulli Trial

• School: University of Guelph
• Department: Statistics
• Course: STAT 2040
• Professor: Jeremy Balka

Document Summary

Ch5 discrete random variables & discrete probability distributions. A random variable is a variable that takes on numerical values according to a chance process. The distribution (prob?) of random variables plays a fundamental role in statistical inference. Probability distribution of a discrete random variable x is a listing of all possible values of x and their probabilities of occurring. The expected value or expectation of a random variable is the theoretical mean random variable, or equivalently, the mean of its probability distribution. of the. Expected value of a function of a random variable. The variance of a discrete random variable is the expectation of its squared distance from the mean: Addition & subtraction of random variables: x &y are independent (additive constant doesn"t affect) Covariance- a measure of the relationship b/t x & y. *the sum of two independent random variables is equal to the variance of the difference of those two random variables.