Statistics is Easy!, Second Edition

Statistics is Easy!, Second Edition

ID:40702453

大小:1.93 MB

页数:174页

时间:2019-08-06

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1、StatisticsisEasy!SecondEditionSynthesisLecturesonMathematicsandStatisticsEditorStevenG.Krantz,WashingtonUniversity,St.LouisStatisticsisEasy!,SecondEditionDennisShashaandMandaWilson2010LecturesonFinancialMathematics:DiscreteAssetPricingGregAndersonandAle

2、cN.Kercheval2010JordanCanonicalForm:TheoryandPracticeStevenH.Weintraub2009TheGeometryofWalkerManifoldsMiguelBrozos-Vázquez,EduardoGarcía-Río,PeterGilkey,StanaNikcevic,andRámonVázquez-Lorenzo2009AnIntroductiontoMultivariableMathematicsLeonSimon2008Jordan

3、CanonicalForm:ApplicationtoDifferentialEquationsStevenH.Weintraub2008StatisticsisEasy!DennisShashaandMandaWilson2008AGyrovectorSpaceApproachtoHyperbolicGeometryAbrahamAlbertUngar2008Copyright©2011byDennisShashaandMandaWilsonAllrightsreserved.Nopartofthi

4、spublicationmaybereproduced,storedinaretrievalsystem,ortransmittedinanyformorbyanymeans—electronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotationsinprintedreviews,withoutthepriorpermissionofthepublisher,Morgan&ClaypoolPublishers.Statis

5、ticsisEasy!,SecondEditionDennisShashaandMandaWilsonwww.morganclaypool.comISBN:9781608455706paperbackISBN:9781608455713ebookDOI:10.2200/S00295ED1V01Y201009MAS008APublicationintheMorgan&ClaypoolPublishers’seriesSYNTHESISLECTURESONMATHEMATICSANDSTATISTICSL

6、ecture#8SeriesEditor:StevenG.Krantz,WashingtonUniversitySt.LouisSeriesISSNSynthesisLecturesonMathematicsandStatisticsPrint:1938-1743Electronic:1938-175110987654321StatisticsisEasy!,SecondEditionDennisShashaDepartmentofComputerScienceCourantInstituteofMa

7、thematicalSciencesNewYorkUniversityMandaWilsonBioinformaticsCoreComputationalBiologyCenterMemorialSloan-KetteringCancerCenterSYNTHESISLECTURESINMATHEMATICSANDSTATISTICS#8ABSTRACTStatisticsistheactivityofinferringresultsaboutapopulationgivenasample.Histo

8、rically,statis-ticsbooksassumeanunderlyingdistributiontothedata(typically,thenormaldistribution)andderiveresultsunderthatassumption.Unfortunately,inreallife,onecannotnormallybesureoftheunderlyingdistribution.Forthatreason,thisboo

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