EC255 Study Guide - Midterm Guide: Random Variable, Countable Set, Exponential Distribution
Document Summary
Random variable - contains the outcomes of a chance equipment. Discrete random variable - set of all possible values is a finite or a countably infinite number of possible values, ex. # of new subscribers to a magazine, determining number of defects in a batch of 50 items (have to be counted and not measured) (all business data) Continuous random variable - takes on values at every point over a given interval, ex. weight of a person, time b/n customer arrivals at a retail outlet (measured and not counted) Probability distributions - table, formula, or graph that describes the values that a random variable can take and their respective probability. Discrete probability distributions - constructed from discrete random variables (binomial and poisson) Continuous probability distributions - based on continuous random variables (uniform, exponential, and normal) Experiment - toss 2 coins, let x = # heads. Use histogram; most common graphical way to depict a discrete distribution.
