sigma统计概念培训

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1、Example(con’t)Atx=4.5,z=(x-m)/=(4.5-5)/1.581=-0.32Atx=8.5,z=(x-m)/=(8.5-5)/1.581=2.21Fromstandardisednormaldistributiontable,atz=-0.32P(4.5)=1-0.6255=0.3745atz=2.21P(8.5)=0.9864Hence,P(4.5x8.5)=0.9864-0.3745=0.6119(approxequalto0.6123bybinomialdistribut

2、ion)天马行空官方博客：http://t.qq.com/tmxk_docin；QQ:1318241189；QQ群：175569632IntroductiontoSamplingWhatispopulationinstatistic?Apopulationinstatisticreferstoallitemsthathavebeenchosenforstudy.Whatisasampleinstatistic?Asampleinstatisticreferstoaportionchosenfromapopulat

3、ion,bywhichthedataobtaincanbeusedtoinferontheactualperformanceofthepopulationPopulationSample2Sample6Sample8Sample1Sample3Sample7Sample4Sample5Symbolsforpopulation和sampleForpopulation,Populationmean=mPopulationsize=NPopulation标准偏差=Forsample,Samplemean=XSampl

4、esize=nSample标准偏差=SSamplingdistribution-adistributionofsamplemeansIfyoutake10samplesoutofthesamepopulations,youwillmostlikelyendupwith10differentsamplemeans和sample标准偏差s.ASamplingdistributiondescribestheprobabilityofallpossiblemeansofthesamplestakenfromthesame

5、population.Populationmean,m=150Samplingdistributionmean,XSample2,meanX2Sample1,meanX1Sample3,meanX3Samplen,meanXnCollectionofsamplemeansm=150Populationdistributionwith=25Whensamplesizeincreases,thestandarderror(orthestddeviationofsamplingdistribution)willget

6、smaller.Sampledistributionwithstderrorxmuchlessthan25(whenn=30)Sampledistributionwithstderrorx<25(whenn=5)Samplingdistribution(con’t)Likeallnormalcurve,thesamplingdistributioncanbedescribedbyitsmean,x和its标准偏差x(whichisalsoknownasstandarderrorofthemean).Assu

7、ch,thestandarderrormeasurestheextenttowhichweexpectthemeansfromdifferentsamplestovaryduetochanceerrorinsampling流程.Standarderror=Population标准偏差/squarerootofsamplesizex=/nCentralLimitTheoremThemeanxofthesamplingdistributionwillapproximatelyequaltothepopulatio

8、nmeanregardlessofthesamplesize.Thelargerthesamplesize,thecloserthesamplemeanistowardsthepopulationmean.2.Thesamplingdistributionofthemeanwillapproachnormalityregardlessoftheactualpopulati