大学生创新实践项目统计分析结果.doc 12页

大学生创新实践项目统计分析结果　　大学生创新实践项目统计分析结果　　xx年11月15日　　入职适应测量分析　　一、项目分析　　一是删除数据不全或不诚实问卷二是通过项目分析，删除几个题项。IndependentSamplesTestLevene"sTestforEqualityofVariancest-testforEqualityor1MeanEqualvariancesassumedF.095Sig..759t3.855df75Sig.(2-tailed).000Difference.86585　　Equalvariancesnotassumedr2EqualvariancesassumedEqualvariancesnotassumedr3EqualvariancesassumedEqualvariancesnotassumedr4EqualvariancesassumedEqualvariancesnotassumedr5EqualvariancesassumedEqualvariancesnotassumedr6EqualvariancesassumedEqualvariancesnotassumedr7EqualvariancesassumedEqualvariancesnotassumedr8EqualvariancesassumedEqualvariancesnotassumedr9EqualvariancesassumedEqualvariancesnotassumedr10EqualvariancesassumedEqualvariancesnotassumedr11EqualvariancesassumedEqualvariancesnotassumedr12EqualvariancesassumedEqualvariancesnotassumedr13EqualvariancesassumedEqualvariancesnotassumedr14EqualvariancesassumedEqual variancesnotassumedr15EqualvariancesassumedEqualvariancesnotassumedr16EqualvariancesassumedEqualvariancesnotassumedr17EqualvariancesassumedEqualvariancesnotassumedr18Equalvariancesassumed11.271.0013.8472.6472.576.3612.6182.627.4443.6723.656.0424.9724.910.0244.5834.459.0142.4312.403.6171.5561.558.0093.4733.375.0004.8014.645.087-1.932-1.956.1713.0283.087.061.356.362.9493.9153.937.329-.116-.116.2521.9661.971.8333.4263.397.0031.75973.0397558.5267574.5347572.1197567.9937558.2337568.5407574.0877557.3927554.2527574.6847573.0637573.2357574.8587573.3407574.3227570.30275.000.010.013.011.010.000.000.000.000.000.000.017.019.124.124.001.001.000.000.057.054.003.003.723.718.000.000.908.908.053.052.001.001.083.86585.55488.55488.55352.55352.71070.71070.97222.972221.010841.01084.57656.57656.36721.36721.76423.76423.99661.99661-.49932-.49932.72629.72629.09011.09011.89160.89160-.02033-.02033.40041.40041.81843.81843.33266.845.5914.2675.3276.277.2537.10216.3483.0081.9143.618.004.9661.334.0459.670　　Equalvariancesnotassumedr19EqualvariancesassumedEqualvariancesnotassumedr20EqualvariancesassumedEqualvariancesnotassumed1.291.2601.7201.2771.280.2774.490 4.42561.5897574.2927566.891.090.205.204.000.000.33266.28862.28862.73442.734421.199　　删除题目8、11、13、15、16、18、19（红字部分）　　二、能否进行因子分析检验？　　KMOandBartlett"sTestKaiser-Meyer-OlkinMeasureofSamplingAdequacy.Bartlett"sTestofSphericityApprox.Chi-SquaredfSig..558197.45878.000　　TotalVarianceExplainedComponent12Total2.1521.792InitialEigenvalues%ofVariance16.55213.783Cumulative%16.55230.335ExtractionSumsofSquaredLoadingsTotal2.1521.792%ofVariance16.55213.783Cumulative%16.55230.335RotTotal1.81.8　　3456789101112131.2871.2331.092.968.931.819.748.600.538.467.3759.8999.4818.4007.4437.1656.2975.7504.6124.1383.5922.88640.23349.71458.11565.55872.72379.02084.77089.38393.52197.114100.0001.2871.2331.0929.8999.4818.40040.23349.71458.1151.31.31.1ExtractionMethod:PrincipalComponentAnalysis.　　RotatedComponentMatrixar9r5r20r3r12r14r10r7r2r4r1r17r61.823.790.493-.290.048.420.072-.025-.168.084.152-.043.0542-.067.040.029.719.712.650.607.074-.066.104.109.063-.009Component3.005.142-.269-.077.040.039.467.786.175-.271.121-.201.4734.023.067.038.041.236-.154.032.075.737.707.417-.013 .0275.109.018-.177.073.153-.245-.048-.042-.124.114.018.764.664ExtractionMethod:PrincipalComponentAnalysis.RotationMethod:VarimaxwithKaiserNormalization.a.Rotationconvergedin5iterations.　　第5因子题项只有两项r17和r6，层面所涵盖的题项内容太少，将之删除似乎较为　　适宜。因为这是一个探索性因子分析，题项删除后因子结构也会随之改变，因而必须再进行一次因子分析，以验证量表的结构效度。RotatedComponentMatrixar9r5r20r3r12r10r14r2r4r1r71.813.776.524-.278.049.049.432-.158.109.150-.073Component2-.051.040.008.741.722.616.615-.041.143.071.0593.025.063-.005.022.233.012-.200.721.710.418.0784-.022.177-.183-.161.036.447.155.161-.322.265.841ExtractionMethod:PrincipalComponentAnalysis.RotationMethod:VarimaxwithKaiserNormalization.a.Rotationconvergedin5iterations.　　再一次因子分析后第4因子只有一个题项。删除。TotalVarianceExplainedComponent12345678910Total2.0911.7441.256.973.911.830.696.589.503.406InitialEigenvalues%ofVariance20.91417.43712.5559.7349.1138.3016.9605.8915.0324.063　　Cumulative%20.91438.35150.90660.64069.75378.05485.01490.90595.937100.000ExtractionSumsofSquared LoadingsTotal2.0911.7441.256%ofVariance20.91417.43712.555Cumulative%20.91438.35150.906RotaTotal1.91.81.3　　TotalVarianceExplainedComponent123Total2.0911.7441.256InitialEigenvalues%ofVariance20.91417.43712.555Cumulative%20.91438.35150.906ExtractionSumsofSquaredLoadingsTotal2.0911.7441.256%ofVariance20.91417.43712.555Cumulative%20.91438.35150.906RotaTotal1.91.81.34.9739.73460.6405.9119.11369.7536.8308.30178.0547.6966.96085.0148.5895.89190.9059.5035.03295.937ExtractionMethod:PrincipalComponentAnalysis.RotatedComponentMatrixaComponent123r11.706.043.026r12.704.011.265r14.665.409-.169R15.663-.321.058R19-.025.811.038R17.109.780.073r20-.044.520.012r4.025.078.729r2-.027-.158.710r1.144.149.413ExtractionMethod:PrincipalComponentAnalysis.RotationMethod:VarimaxwithKaiserNormalization.a.Rotationconvergedin4iterations.　　三、信度检验　　因子1：人际适应ReliabilityStatisticsCronbach"sAlpha.731NofItems4　　因子2：文化适应　　ReliabilityStatisticsCronbach"sAlpha.790NofItems3 　　因子3：能力适应ReliabilityStatisticsCronbach"sAlpha.796NofItems3　　影响因素分析　　IndependentSamplesTesty1EqualvariancesassumedEqualvariancesnotassumedLevene"sTestforEqualityofVariancest-tF.157Sig..693t1.8491.849df8078.5158080.0008073.2788079.9998069.3818074.1118073.5418078.2828079.6898079.8668077.044Sig.(2-tailed).068.068.627.627.322.323.339.339.001.001.018.018.001.001.031.031.766.766.030.030.065.065Me.215.644y2EqualvariancesassumedEqualvariancesnotassumed-.488-.4886.073.016y3EqualvariancesassumedEqualvariancesnotassumed.996.996.007.934y4EqualvariancesassumedEqualvariancesnotassumed.963.9631.543.218y5EqualvariancesassumedEqualvariancesnotassumed3.5153.5156.594.012y6EqualvariancesassumedEqualvariancesnotassumed2.4222.422.856.358y7EqualvariancesassumedEqualvariancesnotassumed3.3713.3711.619.207y8EqualvariancesassumedEqualvariancesnotassumed2.1912.191.509.478y9EqualvariancesassumedEqualvariancesnotassumed-.299-.299.415.521y10EqualvariancesassumedEqualvariancesnotassumed2.2042.2044.420.039y11EqualvariancesassumedEqualvariancesnotassumed1.8731.873 　　y12EqualvariancesassumedEqualvariancesnotassumed.000.984.818.8188079.8878078.0088072.5268079.8968079.1698074.2968076.5858078.6558071.9858078.7718079.6108078.281.416.416.013.013.000.000.006.006.045.045.001.001.000.000.001.001.000.000.021.021.034.035.000.0002.556.114y13EqualvariancesassumedEqualvariancesnotassumed2.5552.5558.254.005y14EqualvariancesassumedEqualvariancesnotassumed6.2216.221.004.950y15EqualvariancesassumedEqualvariancesnotassumed2.8262.826.110.741y16EqualvariancesassumedEqualvariancesnotassumed2.0332.0334.428.039y17EqualvariancesassumedEqualvariancesnotassumed3.3393.339.718.399y18EqualvariancesassumedEqualvariancesnotassumed4.5744.574.915.342y19EqualvariancesassumedEqualvariancesnotassumed3.4813.4819.233.003y20EqualvariancesassumedEqualvariancesnotassumed5.1185.1181.909.171y21EqualvariancesassumedEqualvariancesnotassumed2.3622.362.436.511y22EqualvariancesassumedEqualvariancesnotassumed2.1512.1511.957.166y23EqualvariancesassumedEqualvariancesnotassumed3.9973.997RotatedComponentMatrixay14y19y23y17y13y161.673.663.649.522.420-.0532-.101.291-.136.019-.372.7723.250.047-.103-.137-.062.1414.065-.295.062.156.195-.040Component5.201-.089-.012-.091-.063-.0086 .077-.210.020.188.214-.0587.034.137-.037-.220.142-.0168.107-.181.034-.027-.087-.0519.052-.029-.047.005.029.043y4y9y6y7y20y15y11y21y3y22y2y8y12y18y10y5y1-.005-.010.025.068.220.056-.155-.147.035.110-.130.020-.266.410-.106.139.053-.576-.156-.079.049.046-.014.403.217-.198.111-.061.048-.102.110-.217.231-.042.133-.766.630.014.207.231-.187.367.225-.170.156.008.104-.037.042-.098-.067-.255.143.260.824.454-.092.251.000.064.138.423.048.111-.155-.016-.084-.023-.034.035.168.046-.236.784.586-.426.014-.276-.247-.048-.109.112-.095.221-.043-.094.023.030.103-.181-.024.004.299.690.625-.483.062.010-.068-.139.157.001-.133.056.085.023.294-.130.256.044.172-.353-.265.868-.061.095.162-.301-.087-.053-.192-.116-.035.174.000-.024.035-.167.183.021.014.800.731-.095.095.018.154.065.021-.027-.046.107-.113.068-.145.045-.206-.009-.082.071.833.706-.023ExtractionMethod:PrincipalComponentAnalysis.RotationMethod:VarimaxwithKaiserNormalization.a.Rotationconvergedin18iterations.　　去掉y1和y8　　RotatedComponentMatrixay14y23y19y17y13y16y4y91.673.664.657.469.433-.063.007.0142-.090-.139.257.075-.308.725-.668-.1273.263-.106.075-.188-.041 .169.091-.751Component4.067.074-.254.048.222-.079-.182.122　　5.166-.031-.100-.008-.002-.120-.082.0846.085.018-.278.325.255-.154-.131.0307.089.039-.238.002-.177-.032.000-.1838.094.008-.054-.026-.029.129.156.105　　y6y7y20y2y15y11y21y3y22y12y18y5y10.013.056.261-.175.046-.141-.128.033.104-.238.454.112-.123-.087.141.030-.047.004.506.143-.108.111-.097.091.159-.302.631-.020.211.023.290-.074.357.268-.221.088.021-.086.040.271.781.568.450-.158.180.039-.007.020.134-.112-.161.067.121.093-.241-.128.701.593-.559.009-.372-.079.081.105-.067.065.233-.221-.305.000.023.164.716.612.024-.159.093-.192-.099-.032.108.078.049-.061.033-.199.273.796.670.124-.195.032.004-.051-.287.219-.037.114-.150.171-.105.105.792.697ExtractionMethod:PrincipalComponentAnalysis.RotationMethod:VarimaxwithKaiserNormalization.a.Rotationconvergedin19iterations.DescriptiveStatisticssexy1y2y3y4y5rsumValidN(listwise)N132132132132132132132132Minimum.002.202.201.831.671.502.25Maximum1.004.004.203.835.005.004.25Mean.65153.17733.23032.93533.47953.10233.1908Std.Deviation.47831.37693.39345.43687.70977.62085.32405 　　CorrelationssexPearsonCorrelationSig.(2-tailed)sex1y1.151.085y2-.025.780y3-.011.902y4.196.024*y5.037.670rsum.133.129　　Ny1PearsonCorrelationSig.(2-tailed)Ny2PearsonCorrelationSig.(2-tailed)Ny3PearsonCorrelationSig.(2-tailed)Ny4PearsonCorrelationSig.(2-tailed)Ny5PearsonCorrelationSig.(2-tailed)NrsumPearsonCorrelationSig.(2-tailed)N132.151.085132-.025.780132-.011.902132.196.024132.037.670132.133.129132*1321132.001.995132-.021.808132.024.786132-.039.657132-.056.520132.236.006**132.155.076132.061.490132.042.634132.181.038*132-.053.542132-.101.247132-.178.041132.087.324132.204.019**132.001.995132-.021.808132-.039.657132.155.076132-.053.5421321321132.024.786132-.056.520132.061.490132-.101.2471321321132.236.006132.042.634132-.178.041132***1321132.181.038132.087.324132*1321132.204.019132*1321132*.Correlationissignificantatthe0.05level(2-tailed).**.Correlationissignificantatthe0.01level(2-tailed).CoefficientsStandardizedUnstandardizedCoefficientsModel1(Constant)y52(Constant)y5y33(Constant)y5B2.861.1063.255.110-.1393.691.115　　Std.Error.142.045.227.044.063.392.045.220.211-.187.204CoefficientsBetat20.1812.37114.3522.496 -2.2059.4192.528Sig..000.019.000.014.029.000.013.935.998.9981.000CollinearityStatisticsToleranceVIFa1.001.001.001.06y3sexy1y2y4a.DependentVariable:rsum-.148.084-.093-.085.027.064.059.074.070.041-.200.124-.108-.103.060-2.3041.430-1.252-1.225.659.023.155.213.223.511.939.933.945.990.8651.061.071.051.011.15　　以上是朱洁琴的部分。DescriptiveStatisticsr1r2r3jxValidN(listwise)N132132132132132Minimum2.002.001.332.50Maximum4.004.675.004.08Mean3.16673.09083.31553.1725Std.Deviation.41290.62442.65145.36961CoefficientsStandardizedUnstandardizedCoefficientsModel1(Constant)r22(Constant)r2r1a.DependentVariable:jxB2.262.2951.661.306.179Std.Error.142.045.264.044.067.516.200.498CoefficientsBetat15.9336.5406.2956.9152.681Sig..000.000.000.000.008.991.9911.000CollinearityStatisticsToleranceVIFa1.001.001.00　　ExcludedVariablesCollinearityStatisticsPartialModel1r1r32r3BetaIn.200-.088-.089baacMinimumTolerance.9911.0001.000VIF1.0091.0001.000Tolerance.9911.000.991t2.681-1.155-1.197Sig..008.250.234Correlation.230-.101-.105a.PredictorsintheModel:(Constant),r2b.PredictorsintheModel:(Constant),r2,r1c.DependentVariable:jx 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