文档介绍：11SlideSlideSlides Prepared bySlides Prepared byJOHN S. LOUCKSJOHN S. LOUCKSSt. EdwardSt. Edward’’s Universitys University?? 2002 South-Western/Thomson Learning 2002 South-Western/Thomson Learning22SlideSlideChapter 5Chapter 5 Discrete Probability Distributions Discrete Probability DistributionsnnRandom VariablesRandom VariablesnnDiscrete Probability DistributionsDiscrete Probability DistributionsnnExpected Value and VarianceExpected Value and VariancennBinomial Probability DistributionBinomial Probability DistributionnnPoisson Probability DistributionPoisson Probability DistributionnnHypergeometricHypergeometric Probability Distribution Probability 0 1 2 3 4 0 1 2 3 433SlideSlideRandom VariablesRandom VariablesnnA A random variablerandom variable is a numerical description of the is a numerical description of the e of an of an random variable can be classified as being either A random variable can be classified as being either discrete or continuous depending on the numerical discrete or continuous depending on the numerical values it it A discrete random variablediscrete random variable may assume either a may assume either a finite number of values or an infinite sequence of finite number of values or an infinite sequence of A continuous random variablecontinuous random variable may assume any may assume any numerical value in an interval or collection of numerical value in an interval or collection of : JSL AppliancesExample: JSL AppliancesnnDiscrete random variable with a finite number of Discrete random variable with a finite number of valuesvaluesLet Let xx = number of TV sets sold at the store in one day = number of TV sets sold at the store in one day where where xx can take on 5 values (0, 1, 2, 3, 4) can take on 5 values (0, 1, 2,