采用普通最小二乘法估计模型参数,回归模型为Dependent Variable:QMethod:Least SquaresDate:10/23/11 Time:19:27Sample:1997 2009Included observations:13Variable\x05Coefficient\x05Std.Error\x05t-Statistic\x05Prob.GDP\x05-2.000131\x053.291

采用普通最小二乘法估计模型参数,回归模型为Dependent Variable:QMethod:Least SquaresDate:10/23/11 Time:19:27Sample:1997 2009Included observations:13Variable\x05Coefficient\x05Std.Error\x05t-Statistic\x05Prob.GDP\x05-2.000131\x053.291
采用普通最小二乘法估计模型参数,回归模型为
Dependent Variable:Q
Method:Least Squares
Date:10/23/11 Time:19:27
Sample:1997 2009
Included observations:13
Variable\x05Coefficient\x05Std.Error\x05t-Statistic\x05Prob.
GDP\x05-2.000131\x053.291781\x05-0.607614\x050.5585
E\x0529.07323\x0545.06447\x050.645148\x050.5349
NS\x0523.03745\x0527.64399\x050.833362\x050.4262
C\x0549230.15\x0537801.55\x051.302332\x050.2251
R-squared\x050.966564\x05 Mean dependent var\x05114536.0
Adjusted R-squared\x050.955418\x05 S.D.dependent var\x0519600.33
S.E.of regression\x054138.499\x05 Akaike info criterion\x0519.74171
Sum squared resid\x051.54E+08\x05 Schwarz criterion\x0519.91554
Log likelihood\x05-124.3211\x05 F-statistic\x0586.72239
Durbin-Watson stat\x051.175052\x05 Prob(F-statistic)\x050.000001
给定显著性水平α=0.05,查t分布表,得t0.025（8）=2.306
那个变量显著 那个变量不显著

采用普通最小二乘法估计模型参数,回归模型为Dependent Variable:QMethod:Least SquaresDate:10/23/11 Time:19:27Sample:1997 2009Included observations:13Variable\x05Coefficient\x05Std.Error\x05t-Statistic\x05Prob.GDP\x05-2.000131\x053.291
有两种方法：
1.根据上表的t-Statistic,可以发现,所有变量系数的t检验值都小于t0.025（8）=2.306,均未通过5%显著性水平下的t检验,没有一个解释变量对被解释变量的影响是显著的.
2.通过后面Prob.给出的值可以看出,所有变量系数估计的P值都远远大于显著性水平α=0.05,说明哪个变量都不显著.