因子分析作业格式.docx

信赖度分析将9组数据带入spss进行信赖度分析，得出信赖度分析表。根据以下分析得出，信赖度系数为0.672，因此数据可信。Reliability StatisticsCronbachs AlphaN of Items.6729因子分析数据表中选取了九个数据，分别是：食品，衣着，家庭设备及用品，城镇经济，农村经济，个体经济，一般贸易，来料加工，进料加工 。假设：利用SPSS中因子分析来提取公共因子，分析衡量发展因素的指标得出下表。从KMO and Bartletts Test表中得出，KMO值为0.824，表示适合做因子分析。Bartlett球形度检验的原假设为相关系数矩阵是单位阵，sig值为0.00远小于95%有益水准的sig值0.05，因此拒绝原假设，说明变量之间存在相关关系，适合做因子分析。KMO and Bartletts TestKaiser-Meyer-Olkin Measure of Sampling Adequacy.824Bartletts Test of SphericityApprox. Chi-Square703.993df36Sig.000根据Rotated Component Matrixa可以得出旋转后的因子载荷值，其中旋转方法采用的是Kaiser标准化的正交旋转法。通过因子旋转，各个因子有了比较明确的含义。CommunalitiesInitialExtractionVAR000011.000.993VAR000021.000.996VAR000031.000.988VAR000041.000.980VAR000051.000.996VAR000061.000.952VAR000071.000.991VAR000081.000.993VAR000091.000.989Extraction Method: Principal Component Analysis.Total Variance ExplainedComponentInitial EigenvaluesExtraction Sums of Squared LoadingsRotation Sums of Squared LoadingsTotal% of VarianceCumulative %Total% of VarianceCumulative %Total% of VarianceCumulative %18.09989.98989.9898.09989.98989.9894.15546.16646.1662.5906.55796.546.5906.55796.5463.54439.37885.5453.1882.09298.638.1882.09298.6381.17813.09398.6384.0911.00699.6445.012.13599.7806.010.11099.8907.006.06699.9568.002.02799.9829.002.018100.000Extraction Method: Principal Component Analysis.Component MatrixaComponent123VAR00001.954.187-.217VAR00002.977.081-.189VAR00003.986-.069-.109VAR00004.931-.331-.048VAR00005.940-.334.034VAR00006.932-.247.153VAR00007.988.034.117VAR00008.890.445.047VAR00009.936.250.226Extraction Method: Principal Component Analysis.a. 3 components extracted.Rotated Component MatrixaComponent123VAR00001.489.663.560VAR00002.584.612.529VAR00003.710.538.441VAR00004.867.340.335VAR00005.889.370.262VAR00006.843.465.158VAR00007.679.686.244VAR00008.311.891.321VAR00009.510.841.149Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a. Rotation converged in 6 iterations.Component Transformation MatrixComponent1231.690.632.3532-.702.703.1153.175.327-.929Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 经分析得出下表分析后第一个因子是消费，第二个因子是投资，第三个因子是进出口。经转换后得到具体的因子数每组数据的信赖度如下XiaofeiCase Processing SummaryN%CasesValid29100.0Excludeda0.0Total29100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbachs AlphaN of Items.6312TouziCase Processing SummaryN%CasesValid29100.0Excludeda0.0Total29100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbachs AlphaN of Items.8073JinchukouCase Processing SummaryN%CasesValid29100.0Excludeda0.0Total29100.0a. Listwise deletion based on all variables in the procedure.Reliability StatisticsCronbachs AlphaN of Items.7883所以得出下表多元回归分析假设GDP与进出口额和投资额和消费额之间之间呈Y=aX1+bX2+cX3+d根据SPSS软件里的29组数据进行分析，得到下图Variables Entered/RemovedbModelVariables EnteredVariables RemovedMethod1jinchukou, touzi, xiaofeia.Entera. All requested variables entered.b. Dependent Variable: VAR00010Model SummarybModelRR SquareAdjusted R SquareStd. Error of the EstimateDurbin-Watson1.997a.994.9941548.784961.632a. Predictors: (Constant), jinchukou, touzi, xiaofeib. Dependent Variable: VAR00010ANOVAbModelSum of SquaresdfMean SquareFSig.1Regression1.079E1033.598E91.500E3.000aResidual5.997E7252398734.856Total1.085E1028a. Predictors: (Constant), jinchukou, touzi, xiaofeib. Dependent Variable: VAR00010CoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta1(Constant)120.789644.336.187.853xiaofei9.0282.969.1183.041.004touzi4.125.810.1635.092.000jinchukou.009.001.74116.803.000a. Dependent Variable: VAR00010Residuals StatisticsaMinimumMaximumMeanStd. DeviationNPredicted Value1.6649E36.2334E41.8804E419633.1494829Residual-3.25644E34.35430E3.000001463.4642329Std. Predicted Value-.8732.217.0001.00029Std. Residual-2.1032.811.000.94529a. Dependent Variable: VAR00010得出结论：d值为120.789，在95%的标准水平下sig值