应用回归分析实验报告6

PAGEi实验 报告 软件系统测试报告下载sgs报告如何下载关于路面塌陷情况报告535n,sgs报告怎么下载竣工报告下载 实验课程应用回归分析第6次实验实验日期2012.11.22指导教师王振羽班级基地班学号1007402072姓名张艺璇成绩一、实验目的掌握利用统计软件SAS的REG过程中各种最优准则，选取最好的线性回归方程的方法.掌握SPSS中用前进法、后退法、逐步回归法选择自变量二、实验内容1．在教材习题5.9的问题中，使用直到2004年的数据。(数据在“回归人大数据12-学生.xls：ex5_9-07年”中)，利用统计软件(1)写出修正的复决定系数AdjRSQ最好的三个回归方程，及相应的Cp值、AIC值。(2)写出Cp准则最好的三个回归方程，及相应的AdjRSQ值、AIC值。(3)写出用向前法(进=0.05，0.10)得到的两个回归方程；(4)写出用后退法(退=0.10，0.15)得到的两个回归方程；(5)写出用逐步回归法(进,退=0.05,0.10;0.10,0.15;0.15,0.20)得到的三个回归方程；(6)在你看来，上面写出的回归方程中，哪个最好？(写出理由)本次实验结果随作业交上来。三、实验结果与分析（包括运行结果及其数据分析、解释等）(1)写出修正的复决定系数AdjRSQ最好的三个回归方程，及相应的Cp值、AIC值。用SAS寻找最优子集程序如下：procreg;modely=x1-x6/selection=adjrsq;run;输出部分结果如下：系数a模型非 标准 excel标准偏差excel标准偏差函数exl标准差函数国标检验抽样标准表免费下载红头文件格式标准下载 化系数标准系数tSig.B标准误差试用版1(常量)-1.138.325-3.503.002x1-1.487.136-1.313-10.966.000x21.171.1883.0776.237.000x3-2.4671.258-1.009-1.962.063x4.155.035.2404.445.000x6-.058.018-.057-3.151.005a.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-1.226.345-3.556.002x1-1.455.142-1.285-10.228.000x21.235.2053.2466.027.000x3-2.4751.268-1.012-1.952.065x4.162.036.2514.477.000x5-.061.075-.206-.818.423x6-.053.019-.053-2.761.012a.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-1.199.344-3.491.002x1-1.567.138-1.384-11.394.000x2.808.0352.12423.165.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.007a.因变量:y故修正的复决定系数AdjRSQ最好的三个回归方程为：y=-1.138-1.487x1+1.171x2-2.467x3+0.155x4-0.058x6(cp=5.6693,AIC=-153.1970)y=-1.226-1.455x1+1.235x2-2.475x3+0.162x4-0.061x5-0.053x6(cp=7.0000,AIC=-153.0858)y=-1.199-1.567x1+0.808x2+0.165x4-0.058x6(cp=7.4571,AIC=-150.6537)(2)写出Cp准则最好的三个回归方程，及相应的AdjRSQ值、AIC值。用SAS寻找最优子集程序如下：procreg;modely=x1-x6/selection=cp;run;输出部分结果如下：故Cp准则最好的三个回归方程为：y=-1.138-1.487x1+1.171x2-2.467x3+0.155x4-0.058x6(AdjRSQ=0.9943,AIC=-153.1970)y=-1.226-1.455x1+1.235x2-2.475x3+0.162x4-0.061x5-0.053x6(AdjRSQ=0.9942,AIC=-153.0858)y=-1.199-1.567x1+0.808x2+0.165x4-0.058x6(AdjRSQ=0.9935,AIC=-150.6537)(3)写出用向前法(进=0.05，0.10)得到的两个回归方程；进=0.05：模型汇总模型RR方调整R方标准估计的误差1.974a.949.947.162617462.994b.989.988.076818283.996c.992.991.065515374.997d.995.994.05654776a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。Anovae模型平方和df均方FSig.1回归12.223112.223462.225.000a残差.66125.026总计12.884262回归12.74326.3711079.703.000b残差.14224.006总计12.884263回归12.78634.262992.923.000c残差.09923.004总计12.884264回归12.81443.2041001.833.000d残差.07022.003总计12.88426a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-.015.045-.332.743x2.371.017.97421.499.0002(常量).202.0316.474.000x2.760.0421.99717.970.000x1-1.181.126-1.043-9.383.0003(常量)-1.037.393-2.639.015x2.817.0402.14620.275.000x1-1.553.159-1.371-9.751.000x4.125.039.1933.162.0044(常量)-1.199.344-3.491.002x2.808.0352.12423.165.000x1-1.567.138-1.384-11.394.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.007a.因变量:y故得到的回归方程为：y=-1.199-1.567x1+0.808x2+0.165x4-0.058x6进=0.10:模型汇总模型RR方调整R方标准估计的误差1.974a.949.947.162617462.994b.989.988.076818283.996c.992.991.065515374.997d.995.994.056547765.998e.995.994.05320788a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。Anovaf模型平方和df均方FSig.1回归12.223112.223462.225.000a残差.66125.026总计12.884262回归12.74326.3711079.703.000b残差.14224.006总计12.884263回归12.78634.262992.923.000c残差.09923.004总计12.884264回归12.81443.2041001.833.000d残差.07022.003总计12.884265回归12.82552.565906.011.000e残差.05921.003总计12.88426a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。f.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-.015.045-.332.743x2.371.017.97421.499.0002(常量).202.0316.474.000x2.760.0421.99717.970.000x1-1.181.126-1.043-9.383.0003(常量)-1.037.393-2.639.015x2.817.0402.14620.275.000x1-1.553.159-1.371-9.751.000x4.125.039.1933.162.0044(常量)-1.199.344-3.491.002x2.808.0352.12423.165.000x1-1.567.138-1.384-11.394.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.0075(常量)-1.138.325-3.503.002x21.171.1883.0776.237.000x1-1.487.136-1.313-10.966.000x4.155.035.2404.445.000x6-.058.018-.057-3.151.005x3-2.4671.258-1.009-1.962.063a.因变量:y故得到的回归方程为：y=-1.138-1.487x1+1.171x2-2.467x3+0.155x4-0.058x6(4)写出用后退法(退=0.10，0.15)得到的两个回归方程；退=0.15:模型汇总模型RR方调整R方标准估计的误差1.998a.996.994.053632152.998b.995.994.05320788a.预测变量:(常量),x6,x2,x4,x1,x5,x3。b.预测变量:(常量),x6,x2,x4,x1,x3。Anovac模型平方和df均方FSig.1回归12.82762.138743.222.000a残差.05820.003总计12.884262回归12.82552.565906.011.000b残差.05921.003总计12.88426a.预测变量:(常量),x6,x2,x4,x1,x5,x3。b.预测变量:(常量),x6,x2,x4,x1,x3。c.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-1.226.345-3.556.002x1-1.455.142-1.285-10.228.000x21.235.2053.2466.027.000x3-2.4751.268-1.012-1.952.065x4.162.036.2514.477.000x5-.061.075-.206-.818.423x6-.053.019-.053-2.761.0122(常量)-1.138.325-3.503.002x1-1.487.136-1.313-10.966.000x21.171.1883.0776.237.000x3-2.4671.258-1.009-1.962.063x4.155.035.2404.445.000x6-.058.018-.057-3.151.005a.因变量:y故得到的回归方程为：y=-1.138-1.487x1+1.171x2-2.467x3+0.155x4-0.058x6退=0.10:系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-1.226.345-3.556.002x1-1.455.142-1.285-10.228.000x21.235.2053.2466.027.000x3-2.4751.268-1.012-1.952.065x4.162.036.2514.477.000x5-.061.075-.206-.818.423x6-.053.019-.053-2.761.0122(常量)-1.138.325-3.503.002x1-1.487.136-1.313-10.966.000x21.171.1883.0776.237.000x3-2.4671.258-1.009-1.962.063x4.155.035.2404.445.000x6-.058.018-.057-3.151.005a.因变量:y故得到的回归方程为：y=-1.138-1.487x1+1.171x2-2.467x3+0.155x4-0.058x6(5)写出用逐步回归法(进,退=0.05,0.10;0.10,0.15;0.15,0.20)得到的三个回归方程；进,退=0.05,0.10:模型汇总模型RR方调整R方标准估计的误差1.974a.949.947.162617462.994b.989.988.076818283.996c.992.991.065515374.997d.995.994.05654776a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。Anovae模型平方和df均方FSig.1回归12.223112.223462.225.000a残差.66125.026总计12.884262回归12.74326.3711079.703.000b残差.14224.006总计12.884263回归12.78634.262992.923.000c残差.09923.004总计12.884264回归12.81443.2041001.833.000d残差.07022.003总计12.88426系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-.015.045-.332.743x2.371.017.97421.499.0002(常量).202.0316.474.000x2.760.0421.99717.970.000x1-1.181.126-1.043-9.383.0003(常量)-1.037.393-2.639.015x2.817.0402.14620.275.000x1-1.553.159-1.371-9.751.000x4.125.039.1933.162.0044(常量)-1.199.344-3.491.002x2.808.0352.12423.165.000x1-1.567.138-1.384-11.394.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.007a.因变量:y故得到的回归方程为：y=0.202-1.181x1+0.760x2进,退=0.10,0.15:模型汇总模型RR方调整R方标准估计的误差1.974a.949.947.162617462.994b.989.988.076818283.996c.992.991.065515374.997d.995.994.056547765.998e.995.994.05320788a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。Anovaf模型平方和df均方FSig.1回归12.223112.223462.225.000a残差.66125.026总计12.884262回归12.74326.3711079.703.000b残差.14224.006总计12.884263回归12.78634.262992.923.000c残差.09923.004总计12.884264回归12.81443.2041001.833.000d残差.07022.003总计12.884265回归12.82552.565906.011.000e残差.05921.003总计12.88426a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。f.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-.015.045-.332.743x2.371.017.97421.499.0002(常量).202.0316.474.000x2.760.0421.99717.970.000x1-1.181.126-1.043-9.383.0003(常量)-1.037.393-2.639.015x2.817.0402.14620.275.000x1-1.553.159-1.371-9.751.000x4.125.039.1933.162.0044(常量)-1.199.344-3.491.002x2.808.0352.12423.165.000x1-1.567.138-1.384-11.394.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.0075(常量)-1.138.325-3.503.002x21.171.1883.0776.237.000x1-1.487.136-1.313-10.966.000x4.155.035.2404.445.000x6-.058.018-.057-3.151.005x3-2.4671.258-1.009-1.962.063a.因变量:y故得到的回归方程为：y=0.202-1.181x1+0.760x2进,退=0.15,0.20:模型汇总模型RR方调整R方标准估计的误差1.974a.949.947.162617462.994b.989.988.076818283.996c.992.991.065515374.997d.995.994.056547765.998e.995.994.05320788a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。Anovaf模型平方和df均方FSig.1回归12.223112.223462.225.000a残差.66125.026总计12.884262回归12.74326.3711079.703.000b残差.14224.006总计12.884263回归12.78634.262992.923.000c残差.09923.004总计12.884264回归12.81443.2041001.833.000d残差.07022.003总计12.884265回归12.82552.565906.011.000e残差.05921.003总计12.88426a.预测变量:(常量),x2。b.预测变量:(常量),x2,x1。c.预测变量:(常量),x2,x1,x4。d.预测变量:(常量),x2,x1,x4,x6。e.预测变量:(常量),x2,x1,x4,x6,x3。f.因变量:y系数a模型非标准化系数标准系数tSig.B标准误差试用版1(常量)-.015.045-.332.743x2.371.017.97421.499.0002(常量).202.0316.474.000x2.760.0421.99717.970.000x1-1.181.126-1.043-9.383.0003(常量)-1.037.393-2.639.015x2.817.0402.14620.275.000x1-1.553.159-1.371-9.751.000x4.125.039.1933.162.0044(常量)-1.199.344-3.491.002x2.808.0352.12423.165.000x1-1.567.138-1.384-11.394.000x4.165.037.2554.498.000x6-.058.019-.057-2.979.0075(常量)-1.138.325-3.503.002x21.171.1883.0776.237.000x1-1.487.136-1.313-10.966.000x4.155.035.2404.445.000x6-.058.018-.057-3.151.005x3-2.4671.258-1.009-1.962.063a.因变量:y故得到的回归方程为：y=0.202-1.181x1+0.760x2(6)在你看来，上面写出的回归方程中，哪个最好？(写出理由)