BUSS1020 Lecture Notes - Lecture 5: Binomial Distribution, Countable Set, Continuous Or Discrete Variable
18 Jul 2018
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Random variable (rv): represents possible outcomes from an uncertain event. Discrete random variable: set of all possible outcomes is finite, or countably infinite e. g. number of new subscribers to a magazine, number of bad cheques received by a restaurant, number of absent employees on a given day. Continuous random variable: takes on values at every point in a given interval e. g. temperature, elapsed time between arrivals of bank customers, percent of the labour force that is unemployed, financial returns. A probability distribution for a discrete variable is a mutually exclusive and collectively exhaustive list of all the possible numerical outcomes along with the probability of occurrence of each outcome. The expected value of a random variable is the mean, , of its probability distribution. To calculate the expected value, you multiply each possible outcome, xi, by its corresponding probability, p (x = xi), and then sum these products. Variance and standard deviation of a discrete variable:
