多元线性回归实验报告3.3
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南昌大学实验报告
学生姓名学号:专业班级:
座位号:
实验类型:□验证□综合□设计□创新实验日期:2014-4-15 实验成绩:(以下主要内容由学生完成)
一、实验项目名称:线形回归计算机习题C*3.3*
二、实验目的:能在Eview 环境下实现多元线形回归,并理解和掌握相关概念。
三、实验基本原理:最小二乘法
四、主要仪器设备及耗材:EView软件电脑
五、实验数据(按题目填写相应数据文件的名称):
CEOSAL2.RAW
六、实验步骤及处理结果
(i)估计模型:log(salagy)=β0+β1*log(sales)+β2*log(mktval)+u
方程分析:
Variable Coefficient Std. Error t-Statistic Prob.
LOGSALES 0.162128317
6197181
0.0396702551
6261754
4.0868987848
73367
6.66543376
0105512e-0
5
LOGMKTVAL 0.106707985
6006795
0.0501239701
2900644
2.1288813580
81573
0.03467096
293295066
C 4.620917416
339143
0.2544082529
371958
18.163394319
91572
4.95321390
9715841e-4
2
R-squared 0.299113615
9986988 Mean dependent var
6.58284755
171243
Adjusted R-squared 0.291057450
6653504 S.D. dependent var
0.60605944
62305454
S.E. of regression 0.510294333
7280782 Akaike info criterion
1.50914574
8576171
Sum squared resid 45.30965342
408709 Schwarz criterion
1.56297879
4890982
Log likelihood -130.559398 Hannan-Quinn criter. 1.53097834
7489911 1288743
F-statistic 37.12853493
218736 Durbin-Watson stat
2.09211535
5929015
Prob(F-statistic) 3.726861125 125264e-14
Estimation Command:
=========================
LS LSALARY LSALES LMKTVAL PROFITS C
Estimation Equation:
=========================
LSALARY = C(1)*LSALES + C(2)*LMKTVAL + C(3)*PROFITS + C(4)
Substituted Coefficients:
=========================
LSALARY = 0.161368279087*LSALES + 0.0975285405136*LMKTVAL + 3.56600622423e-05*PROFITS + 4.68692448206
可得回归方程为:
Log(salagy)= 0.16212831762*log(sales)+ 0.106707985601*log(lmktval) + 4.62091741634
(ii)方程分析:
Variable Coefficient Std. Error t-Statistic Prob.
LOGSALES 0.161368268
3358957
0.0399100513
7337053
4.0432989380
60666
7.92318025
659531e-05
LOGMKTVAL 0.097528575
01212135
0.0636886362
3577047
1.5313340146
1256
0.12751342
04067937
PROFITS 3.566006940
107313e-05
0.0001519598
750509365
0.2346676672
97831
0.81474419
62293917
C 4.686924327
383991
0.3797294078
487457
12.342800506
11959
1.65015641
0192563e-2
5
R-squared 0.299336649
350446 Mean dependent var
6.58284755
171243
Adjusted R-squared 0.287186417
8362919 S.D. dependent var
0.60605944
62305454
S.E. of regression 0.511685614
9669119 Akaike info criterion
1.52012691
6834263
Sum squared resid 45.29523516
158356 Schwarz criterion
1.59190431
1920678