华理多元统计实验1

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1、华东理工大学2013—2014学年第二学期《多元统计学》实验报告7班级学号姓名开课学院商学院任课教师任6成绩实验内容：实验5因子分析方法1.“主成分分析”的计算机实现2.“因子分析”的计算机实现实验要求：1.熟悉SPSS中主成分分析功能2.熟悉SPSS中因子分析功能3.选用数据文件datal5-01，利用因子分析的新变量，进行聚类分析教师评语：教师签名：年月曰实验报告：1.主成分分析Analyze-DimensionReduction-FactorDataTransformAnalyzeDirectMarketingGraphsUtilitiesAdd-onsW

2、indowHelp!rsexageit(112121213220412151216121112181239122012111202121312341215119ReportsDescriptiveStatisticsTablesCompareMeansGeneralLinearModelGeneralizedLinearModelsMixedModelsCorrelateRegressionLoglinearNeuralNetworksClassifyDimensionReductionScaleNonparametricTestsForecastingSurv

3、ivalFvlultipleResponsex5x6x7x8[x9]x10x11x12x13x144444232444/23443444545/2244324445%5314344241/%1212224344L4414435342r43424232424/%4414434232/AAc4533岔factor...4544z0CorrespondenceAnalysis...4455-OptimalScaling...4544r%54243344454444224222z4233444443zMethod:丄FactorAnalysisAnalyze@Corre

4、lationmatrix◎CovariancematrixDisplay4Unrotatedfactorsolution□Screeplotb4b4z4b4b15514255353j[OKjPaste(ResetjCancel[HelpjExtractS)BasedonEigenvalueEigenvaluesgreaterthan:◎FixednumberoffactorsFactorstoextract:MaximumIterationsforConvergence:

5、25

6、[ContinuejkCanceljHelp得到实验结果如下:Correlation

7、ssexageitemranksexPearsonCorrelation1-.140".034-.043Sig.(2-tailed).013.547.445N312312312312agePearsonCorrelation-.140"1.107-.253"Sig.(2-tailed).013.058.000N312312312312itemPearsonCorrelation.034.1071-.273"Sig.(2-tailed).547.058.000N312312312312rankPearsonCorrelation-.043-.253"-.273"1

8、Sig.(2-tailed).445.000.000N312312312312*.Correlationissignificantatthe0.05level(2-tailed).**.Correlationissignificantatthe0.01level(2-tailed).CommunalitiesInitialExtractionsex1.000.762age1.000.605item1.000.525rank1.000.632ExtractionMethod:PrincipalComponentAnalysis.表1屮的相关系数表明四个变鲎之间存在

9、显著相关性，可以进行主成分分析；表2为变量共同度，表屮最后一列都大于0.5,表明四个变量之间存在着一定的相关性;TotalVarianceExplainedComponentInitialEigenvaluesExtractionSumsofSquaredLoadingsTotal%ofVarianceCumulative%Total%ofVarianceCumulative%11.43135.78635.7861.4313578635.78621.09327.32863.1131.09327.32863.1133.81920.47183.5854.65716.

10、415100.000Ex