MGMT 1050 Chapter 7: Chapter 7 - Random Variables and Discrete Probability Distributions
Document Summary
Chapter 7: random variables and discrete probability distribution. Random variable: a function or rule that assigns a number to each outcome of an experiment: ex. When flipping two coins, 4 different possibilities can occur. However, if you count the number of heads, the random variables are 0, 1, 2 heads: ex. the sum of two dices, when the random variable is defined as x, x=2, 3, 4, 5, 6, Discrete random variable: one that can take countable number of values. Continuous random variable: values are uncountable: ex. the time it takes to finish a university exam. Probability distribution: table, formula, graph that describes the values of a random variable and the probability associated with these variables. Let x represents a variable, and to find the probability, the notation is p(x) Probabilities of the values of discrete random variable may be derived by probability tools like tree diagrams. For situations in which discrete values are used.
