STAT 1100 Chapter 7: Chpt. 7 - Random Variables and Discrete Probability Distributions
Document Summary
Chapter 7: random variables and discrete probability. Section 1 random variables and probability distributions. Random variable: a function or rule that assigns a number to each outcome of an experiment. Two types of random variables: 1. Discrete random variable: one that can take on a countable number of values: 2. Continuous random variable: one whose values are uncountable. Requirements for a distribution of a discrete random variable: 1. 0 p(x) 1 for all x: 2. Where the random variable can assume values x and p(x) is the probability that. Probability distributions and populations the random variable is equal to x. Importance of probability distributions derives from their use as representatives of populations. Population mean: weighted average of all of its values: e(x, e(x) = = xp(x) Population variance: the weighted average of the squared deviations from the mean: v(x) = 2 = (x- )2p(x, shortcut calculation for population variance. V(x) = 2 = x2p(x) 2. Population standard deviation: = 2.
