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时间:2020-07-30
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1、CHAPTER6DiscreteProbabilityDistributionstoaccompanyIntroductiontoBusinessStatisticsfourthedition,byRonaldM.WeiersPresentationbyPriscillaChaffe-StengelDonaldN.Stengel©2002TheWadsworthGroupChapter6-LearningObjectivesDistinguishbetweendiscreteandcontinuousran
2、domvariables.DifferentiatebetweenthebinomialandthePoissondiscreteprobabilitydistributionsandtheirapplications.Constructaprobabilitydistributionforadiscreterandomvariable,determineitsmeanandvariance,andspecifytheprobabilitythatadiscreterandomvariablewillhave
3、agivenvalueorvalueinagivenrange.©2002TheWadsworthGroupChapter6-KeyTermsRandomvariablesDiscreteContinuousBernoulliprocessProbabilitydistributionsBinomialdistributionPoissondistribution©2002TheWadsworthGroupDiscretevsContinuousVariablesDiscreteVariables:Canta
4、keononlycertainvaluesalonganintervalthenumberofsalesmadeinaweekthevolumeofmilkboughtatastorethenumberofdefectivepartsContinuousVariables:Cantakeonanyvalueatanypointalonganintervalthedepthatwhichadrillingteamstrikesoilthevolumeofmilkproducedbyacowtheproporti
5、onofdefectiveparts©2002TheWadsworthGroupDescribingtheDistributionforaDiscreteRandomVariableTheprobabilitydistributionforadiscreterandomvariabledefinestheprobabilityofadiscretevaluex.Mean:µ=E(x)=Variance:s2=E[(x–µ)2]=©2002TheWadsworthGroupTheBernoulliProcess
6、,CharacteristicsTherearetwoormoreconsecutivetrials.Ineachtrial,therearejusttwopossibleoutcomes.Thetrialsarestatisticallyindependent.Theprobabilityofsuccessremainsconstanttrial-to-trial.©2002TheWadsworthGroupTheBinomialDistributionThebinomialprobabilitydist
7、ributiondefinestheprobabilityofexactlyxsuccessesinntrialsoftheBernoulliprocess.foreachvalueofx.Mean:µ=E(x)=npVariance:s2=E[(x–µ)2]=np(1–p)©2002TheWadsworthGroupTheBinomialDistribution,AnExampleWorkedbyEquationProblem6.23:AstudybytheInternationalCoffeeAssoc
8、iationfoundthat52%oftheU.S.populationaged10andoverdrinkcoffee.Forarandomlyselectedgroupof4individuals,whatistheprobabilitythat3ofthemarecoffeedrinkers?NumberProportionCoffeedrinkers(x)3.52Noncoffeedrin
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