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ID:40702461
大小:6.03 MB
页数:719页
时间:2019-08-06
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1、Statistics:MethodsandApplicationsByPawelLewickiandThomasHillChapter1ElementaryConceptsChapter2BasicStatisticsChapter3ANOVA/MANOVAChapter4AssociationRulesChapter5BoostingTreesChapter6CanonicalAnalysisChapter7CHAIDAnalysisChapter8ClassificationandRegressionTrees
2、(C&RT)Chapter9ClassificationTreesChapter10ClusterAnalysisChapter11CorrespondenceAnalysisChapter12DataMiningTechniquesChapter13DiscriminantFunctionAnalysisChapter14DistributionFittingChapter15ExperimentalDesign(IndustrialDOE)Chapter16PrincipalComponentsandFacto
3、rAnalysisChapter17GeneralDiscriminantAnalysis(GDA)Chapter18GeneralLinearModels(GLM)Chapter19GeneralizedAdditiveModels(GAM)Chapter20GeneralizedLinearModels(GLZ)Chapter21GeneralRegressionModels(GRM)Chapter22SelectedTopicsinGraphicalAnalyticTechniquesChapter23Ind
4、ependentComponentsAnalysisChapter24MultipleRegressionChapter25Log-LinearAnalysisofFrequencyTablesMultivariateAdaptiveRegressionSplinesChapter26(MARSplines)Chapter27MachineLearning1Chapter28MultidimensionalScalingChapter29NeuralNetworksChapter30NonlinearEstimat
5、ionChapter31NonparametricStatisticsChapter32PartialLeastSquares(PLS)Chapter33PowerAnalysisChapter34ProcessAnalysisChapter35QualityControlChartsChapter36ReliabilityandItemAnalysisChapter37StructuralEquationModelingChapter38Survival/FailureTimeAnalysisChapter39T
6、extMiningChapter40TimeSeriesAnalysisVarianceComponentsandMixedModelChapter41ANOVA/ANCOVAChapter42DistributionTablesReferences2Chapter1ElementaryConceptsinStatisticsOverviewofElementaryConceptsinStatistics.Inthisintroduction,wewillbrieflydiscussthoseelementarys
7、tatisticalconceptsthatprovidethenecessaryfoundationsformorespecializedexpertiseinanyareaofstatisticaldataanalysis.Theselectedtopicsillustratethebasicassumptionsofmoststatisticalmethodsand/orhavebeendemonstratedinresearchtobenecessarycomponentsofone'sgeneralund
8、erstandingofthe"quantitativenature"ofreality(Nisbett,etal.,1987).Becauseofspacelimitations,wewillfocusmostlyonthefunctionalaspectsoftheconceptsdiscussedandthepresentationwillbevery
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