课内作业VIP

陈振坤 2015020141 多元正态分布的估计与检验Chapter 2 样本均值的计算Descriptive StatisticsNMean地区生产总值2016830963.10固定资产投资2018987692.35社会消费品零售总额206857594.05货物进出口总额201059096.200000外商直接投资实际使用额2046204.65规模以上工业总产值2024937875.25公共财政预算收入20135.305500Valid N (listwise)20样本协方差阵的计算Correlations地区生产总值固定资产投资社会消费品零售总额货物进出口总额外商直接投资实际使用额规模以上工业总产值公共财政预算收入地区生产总值Pearson Correlation1.709*.930*.646*.747*.954*.874*Sig. (2-tailed).000.000.002.000.000.000Sum of Squares and Cross-products2780497562810982.5006894095249929629.0001290890046227157.500255581128369375.7508879371843563.7014227602479998554.00023453214989.979Covariance146341976990051.720362847118417348.90067941581380376.71013451638335230.303467335360187.563222505393684134.4001234379736.315N20202020202020固定资产投资Pearson Correlation.709*1.526*.275.482*.809*.439Sig. (2-tailed).000.017.240.031.000.053Sum of Squares and Cross-products6894095249929629.00034028526278026752.0002552058038390319.000381210859362129.60020056415018646.45012546547031245676.00041188963794.991Covariance362847118417348.9001790975067264566.000134318844125806.27020063729440112.0861055600790455.076660344580591877.6002167840199.736N20202020202020社会消费品零售总额Pearson Correlation.930*.526*1.536*.584*.833*.801*Sig. (2-tailed).000.017.015.007.000.000Sum of Squares and Cross-products1290890046227157.5002552058038390319.000692852443029998.800105877436180023.5503467126129392.3511842584246179450.80010730571780.125Covariance67941581380376.710134318844125806.27036465918054210.4605572496641053.871182480322599.59796978118219971.100564766935.796N20202020202020货物进出口总额Pearson Correlation.646*.275.536*1.813*.640*.891*Sig. (2-tailed).002.240.015.000.002.000Sum of Squares and Cross-products255581128369375.750381210859362129.600105877436180023.55056339021695837.0601376229019938.500403477250239606.7003403223533.503Covariance13451638335230.30320063729440112.0865572496641053.8712965211668201.95172433106312.55321235644749452.984179117028.079N20202020202020外商直接投资实际使用额Pearson Correlation.747*.482*.584*.813*1.759*.881*Sig. (2-tailed).000.031.007.000.000.000Sum of Squares and Cross-products8879371843563.70120056415018646.4503467126129392.3511376229019938.50050801081906.55014372621004921.750100989046.228Covariance467335360187.5631055600790455.076182480322599.59772433106312.5532673741152.976756453737101.1455315212.959N20202020202020规模以上工业总产值Pearson Correlation.954*.809*.833*.640*.759*1.816*Sig. (2-tailed).000.000.000.002.000.000Sum of Squares and Cross-products4227602479998554.00012546547031245676.0001842584246179450.800403477250239606.70014372621004921.7507062377873402697.00034894863926.322Covariance222505393684134.400660344580591877.60096978118219971.10021235644749452.984756453737101.145371704098600141.9401836571785.596N20202020202020公共财政预算收入Pearson Correlation.874*.439.801*.891*.881*.816*1Sig. (2-tailed).000.053.000.000.000.000Sum of Squares and Cross-products23453214989.97941188963794.99110730571780.1253403223533.503100989046.22834894863926.322258705.857Covariance1234379736.3152167840199.736564766935.796179117028.0795315212.9591836571785.59613616.098N20202020202020*. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).Chapter 3 多元正态分布均值向量和协差阵的检验第4节 实例分析与计算机实现Tests of NormalityKolmogorov-SmirnovaShapiro-WilkStatisticdfSig.StatisticdfSig.总资产贡献率.13331.173.97731.713资产负债率.11431.200*.87531.002流动资产周转次数.10831.200*.97331.618工业成本费用利润率.20131.002.88331.003产品销售率.19631.004.90531.010*. This is a lower bound of the true significance.a. Lilliefors Significance Correction取对数之后的检验：Case Processing SummaryCasesValidMissingTotalNPercentNPercentNPercent资产负债率3196.9%13.1%32100.0%工业成本费用利润率3196.9%13.1%32100.0%产品销售率3196.9%13.1%32100.0%log总资产贡献率3196.9%13.1%32100.0%log流动资产周转率3196.9%13.1%32100.0%多元正态分布的均值向量检验主体间因子表Between-Subjects FactorsN类别 111 28 312主体间因子表中展示了三类的样品个数。协差阵的方差齐性检验Boxs Test of Equality of Covariance MatricesaBoxs M71.755F1.720df130df21874.705Sig.009Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups.a. Design: Intercept + 类别多变量检验表Multivariate TestsaEffectValueFHypothesis dfError dfSig.InterceptPillais Trace1.00033002.834b5.00024.000.000Wilks Lambda.00033002.834b5.00024.000.000Hotellings Trace6875.59033002.834b5.00024.000.000Roys Largest Root6875.59033002.834b5.00024.000.000类别Pillais Trace.6632.47710.00050.000.017Wilks Lambda.4032.759b10.00048.000.009Hotellings Trace1.3173.02810.00046.000.005Roys Largest Root1.1785.890c5.00025.000.001a. Design: Intercept + 类别b. Exact statisticc. The statistic is an upper bound on F that yields a lower bound on the significance level.主体间效应检验表：Tests of Between-Subjects EffectsSourceDependent VariableType III Sum of SquaresdfMean SquareFSig.Corrected Model资产负债率71.653a235.826.770.472工业成本费用利润率32.309b216.1552.126.138产品销售率32.277c216.1394.847.016log总资产贡献率.103d2.0512.676.086log流动资产周转率.192e2.0964.760.017Intercept资产负债率100882.1091100882.1092169.336.000工业成本费用利润率1905.69111905.691250.768.000产品销售率287225.4031287225.40386264.926.000log总资产贡献率40.059140.0592091.388.000log流动资产周转率4.21014.210208.398.000类别资产负债率71.653235.826.770.472工业成本费用利润率32.309216.1552.126.138产品销售率32.277216.1394.847.016log总资产贡献率.1032.0512.676.086log流动资产周转率.1922.0964.760.017Error资产负债率1302.1032846.504工业成本费用利润率212.784287.599产品销售率93.228283.330log总资产贡献率.53628.019log流动资产周转率.56628.020Total资产负债率105650.79631工业成本费用利润率2248.98231产品销售率295759.90531log总资产贡献率41.24431log流动资产周转率4.80931Corrected Total资产负债率1373.75630工业成本费用利润率245.09330产品销售率125.50530log总资产贡献率.63930log流动资产周转率.75830a. R Squared = .052 (Adjusted R Squared = -.016)b. R Squared = .132 (Adjusted R Squared = .070)c. R Squared = .257 (Adjusted R Squared = .204)d. R Squared = .160 (Adjusted R Squared = .100)e. R Squared = .254 (Adjusted R Squared = .200)多元正态分布协差阵的检验Levenes Test of Equality of Error VariancesaFdf1df2Sig.总资产贡献率.757228.479资产负债率.573228.570流动资产周转次数1.010228.377工业成本费用利润率10.027228.001产品销售率3.114228.060Tests the null hypothesis that the error variance of the dependent variable is equal across groups.a. Design: Intercept + 类别Tests of Between-Subjects EffectsSourceDependent VariableType III Sum of SquaresdfMean SquareFSig.Corrected Model总资产贡献率105.112a252.5563.578.041资产负债率71.653b235.826.770.472流动资产周转次数5.583c22.7926.484.005工业成本费用利润率32.309d216.1552.126.138产品销售率32.277e216.1394.847.016Intercept总资产贡献率6720.67616720.676457.493.000资产负债率100882.1091100882.1092169.336.000流动资产周转次数188.4151188.415437.669.000工业成本费用利润率1905.69111905.691250.768.000产品销售率287225.4031287225.40386264.926.000类别总资产贡献率105.112252.5563.578.041资产负债率71.653235.826.770.472流动资产周转次数5.58322.7926.484.005工业成本费用利润率32.309216.1552.126.138产品销售率32.277216.1394.847.016Error总资产贡献率411.3262814.690资产负债率1302.1032846.504流动资产周转次数12.05428.430工业成本费用利润率212.784287.599产品销售率93.228283.330Total总资产贡献率7152.75331资产负债率105650.79631流动资产周转次数201.02931工业成本费用利润率2248.98231产品销售率295759.90531Corrected Total总资产贡献率516.43830资产负债率1373.75630流动资产周转次数17.63730工业成本费用利润率245.09330产品销售率125.50530a. R Squared = .204 (Adjusted R Squared = .147)b. R Squared = .052 (Adjusted R Squared = -.016)c. R Squared = .317 (Adjusted R Squared = .268)d. R Squared = .132 (Adjusted R Squared = .070)e. R Squared = .257 (Adjusted R Squared = .204)思考与练习：3.3计算样本均值向量、样本离差阵、协差阵、相关阵（方差分析前要做正态性检验）均值向量Descriptive StatisticsNMeanX1208.15X2205.10X3204.45X4207.10Valid N (listwise)20样本协差阵、样本离差阵、样本相关阵CorrelationsX1X2X3X4X1Pearson Correlation1-.564*-.314-.116Sig. (2-tailed).010.178.625Sum of Squares and Cross-products28.550-23.300-16.350-4.300Covariance1.503-1.226-.861-.226N20202020X2Pearson Correlation-.564*1.333.034Sig. (2-tailed).010.151.888Sum of Squares and Cross-products-23.30059.80025.1001.800Covariance-1.2263.1471.321.095N20202020X3Pearson Correlation-.314.3331.209Sig. (2-tailed).178.151.376Sum of Squares and Cross-products-16.35025.10094.95014.100Covariance-.8611.3214.997.742N20202020X4Pearson Correlation-.116.034.2091Sig. (2-tailed).625.888.376Sum of Squares and Cross-products-4.3001.80014.10047.800Covariance-.226.095.7422.516N20202020*. Correlation is significant at the 0.01 level (2-tailed).3.4均值向量的检验提出假设：Between-Subjects FactorsN总体类别1.00202.0020Descriptive Statistics总体类别MeanStd. DeviationNX11.008.151.226202.007.00.00020Total7.571.03540X21.005.101.774202.005.00.00020Total5.051.23940X31.004.452.235202.004.00.00020Total4.231.57740X41.007.101.586202.008.00.00020Total7.551.19740Multivariate TestsaEffectValueFHypothesis dfError dfSig.InterceptPillais Trace.9962448.983b4.00035.000.000Wilks Lambda.0042448.983b4.00035.000.000Hotellings Trace279.8842448.983b4.00035.000.000Roys Largest Root279.8842448.983b4.00035.000.000sPillais Trace.4878.309b4.00035.000.000Wilks Lambda.5138.309b4.00035.000.000Hotellings Trace.9508.309b4.00035.000.000Roys Largest Root.9508.309b4.00035.000.000a. Design: Intercept + sb. Exact statistic3.5在显著性水平为下检验男女婴儿的两项指标是否有差异。提出假设：Between-Subjects FactorsN性别1.00152.0015Descriptive Statistics性别MeanStd. DeviationNX11.0075.20018.3067152.0073.16716.932315Total74.18317.357030X21.008.58334.80482152.008.11674.4086615Total8.35004.5370130Multivariate TestsaEffectValueFHypothesis dfError dfSig.InterceptPillais Trace.9942398.438b2.00027.000.000Wilks Lambda.0062398.438b2.00027.000.000Hotellings Trace177.6622398.438b2.00027.000.000Roys Largest Root177.6622398.438b2.00027.000.000gPillais Trace.005.062b2.00027.000.940Wilks Lambda.995.062b2.00027.000.940Hotellings Trace.005.062b2.00027.000.940Roys Largest Root.005.062b2.00027.000.940a. Design: Intercept + gb. Exact statistic3.63.7Between-Subjects FactorsValue LabelN类别1.00第一个小时162.00第二个小时163.00第三个小时16Descriptive Statistics类别MeanStd. DeviationN低频心电第一个小时4.8231.7041216第二个小时4.7969.6174816第三个小时4.8494.5918316Total4.8231.6262348高频心电第一个小时3.6200