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1、数据模型与决策作业一、 Cropain公司基建部问题1、首先将60组数据单独列出，找到因变量Y（earn）和自变量X（size、p15、inc、nrest、price）,数据如下所示：STOREARNSIZEP15INCNRESTPRICE128.312998027.64516.102-1.591129028.32711.40368.9140294030.2521.704202.1184357027.6711.805115.8144170033.92516.606221.7160464032.5822.107292.994360033.18924.308134.4100345029.71416
2、.40937.485193028.44312.9010181.092352028.37613.0011246.9167397038.3922.8012178.3199319032.11110.1013214.983492036.0816.70140.6141121035.31131.0015252.3240415035.91614.0016124.282279033.4613.3017258.196418035.4912.3018193.078465029.75128.801954.899132028.81712.802045.475221029.81321.702166.352418028.
3、62615.9022123.7177145034.91412.902357.8111167026.44111.702475.28472028.06416.7025115.695262028.25010.9026140.995399029.62123.202794.167349026.91816.0028250.8154395027.76414.3029-43.093257025.2533.4030145.667199036.56111.1031147.661479032.8317.7032175.1116446027.71912.9033117.992205033.6511.203479.57
4、8337029.54520.0035140.5103245034.91332.9036399.2191485034.59618.2037246.3263288038.82922.603877.626177031.01320.6039108.3169177031.81019.3040188.697433030.82910.5041143.5117331029.93619.5042175.5116155034.04412.504394.176405031.01911.7044214.2144392030.0267.604563.387323025.53218.7046237.173515035.2
5、1410.5047208.859345034.47111.7048110.683407029.54425.0049165.4125280033.81211.3050-11.456215029.91214.1051216.3146280032.12611.605265.762202032.77018.005367.696232030.0713.6054127.986248034.41716.505582.988187028.81612.8056-2.972331028.71024.3057247.7119362033.46313.3058343.0285416027.64018.3059193.
6、1193195028.73412.5060277.592489036.03114.10打开EXCEL表格-工具-数据分析-回归-确定-Y值区域为EARN列，X值区域为SIZE到PRICE列，点标志-确定，生成数据如下：SUMMARY OUTPUT回归统计Multiple R0.92532R Square0.856217Adjusted R Square0.842903标准误差36.20023观测值60方差分析dfSSMSFSignificance F回归分析5421397.184279.4164.3131.64E-21残差5470764.671310.457总计59492161.7Coeffi
7、cients标准误差t StatP-valueLower 95%Upper 95%下限 95.0%上限 95.0%Intercept-353.8248.33297-7.320471.24E-09-450.722-256.918-450.722-256.918SIZE0.7718770.0896468.61031.03E-110.5921480.9516060.5921480.951606P150.0441750.00403510.947862.52E-150.0360860.0522650.0360860.052265INC8.7764911.4859285.9064022.41E-075.7
8、9738411.75565.79738411.7556NREST1.4126480.2104936.7111471.21E-080.9906351.8346610.9906351.834661PRICE-2.685310.796325-3.372130.001385-4.28185-1.08878-4.28185-1.08878回归方程如下：Y(earn)=0.77size+0.04p15+8.78inc+1.41nrest-2.69price-353.82多重共线性检验如下：回到EXCEL表格-工具-数据分析-相关系数-确定,选定区域为从EARN到PRICE的所有列,点击标志在第一行,确定,
9、生成相关性系数.EARNSIZEP15INCNRESTPRICEEARN1SIZE0.4366231P150.62823-0.052861INC0.4649430.1802740.1549231NREST0.337582-0.096390.067913-0.058251PRICE-0.180020.066436-0.025470.004017-0.0634512、将Y变量（earn）和X变量（从size到price）粘贴到MINITAB中，统计-回归-逐步回归-响应（earn），预测变量（从size到price）-确定，得出数据如下：逐步回归: EARN 与 SIZE, P15, INC, N
10、REST, PRICE 入选用 Alpha: 0.15 删除用 Alpha: 0.15响应为 5 个自变量上的 EARN，N = 50步骤 1 2 3 4 5常量 -0.6348 -354.7460 -421.2498 -412.5582 -379.4336P15 0.0459 0.0416 0.0397 0.0436 0.0432T 值 5.81 6.35 7.20 10.00 10.49P 值 0.000 0.000 0.000 0.000 0.000INC 11.7 12.8 9.7 9.7T 值 4.93 6.37 5.85 6.19P 值 0.000 0.000 0.000 0.000NREST 1.33 1.48 1.46T 值 4.56 6.43 6.70P 值 0.000 0.000 0.000SIZE 0.61 0.63T 值 5.51 6.04P 值 0.000 0.000PRICE -2.01
