MGMT 1050 Chapter Notes - Chapter 7: Continuous Or Discrete Variable, Random Variable, Standard Deviation
Document Summary
Random variable is a function or rule that assigns a number to each outcome of a experiment. Simply stated the value of a random variable is a numerical event. There are two types of random variables: discrete and continuous. A continuous random variable is not countable. Probability distribution is a table, formula, or graph that describes the values of a random variable and the probability of these values. Probability distribution is important because it provides us information of a population (probability distribution often represents population) The population mean is also called the expected value of x. Requirements for discrete random variable: 0 less than or equal to p(x) less than or equal to 1, for all x, p(x) = 1, all x. If properties 2, 3, and 4 are satisfied, we say that each trial is a bernoulli process. X is the random variable representing success, it is called the binomial random variable.
