1、对x1一个解释变量做回归,显著。
reg y x1
Source | SS df MS Number of obs = 31
-------------+------------------------------ F( 1, 29) = 164.59
Model | 627421.854 1 627421.854 Prob > F = 0.0000
Residual | 110547.565 29 3811.98502 R-squared = 0.8502
-------------+------------------------------ Adj R-squared = 0.8450
Total | 737969.419 30 24598.9806 Root MSE = 61.741
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y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .0055948 .0004361 12.83 0.000 .0047029 .0064867
_cons | 35.94047 17.71793 2.03 0.052 -.2967588 72.1777
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2、加入一个新的解释变量x2,显著。
reg y x1 x2
Source | SS df MS Number of obs = 31
-------------+------------------------------ F( 2, 28) = 90.67
Model | 639267.179 2 319633.59 Prob > F = 0.0000
Residual | 98702.2402 28 3525.08001 R-squared = 0.8663
-------------+------------------------------ Adj R-squared = 0.8567
Total | 737969.419 30 24598.9806 Root MSE = 59.372
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y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .0042212 .0008587 4.92 0.000 .0024622 .0059801
x2 | .0134095 .0073152 1.83 0.077 -.0015749 .028394
_cons | 18.55874 19.49892 0.95 0.349 -21.38298 58.50046
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3、加入第3个解释变量,请问为啥之前两个解释变量就不显著了呢?由什么问题引起的的?
reg y x1 x2 x3
Source | SS df MS Number of obs = 31
-------------+------------------------------ F( 3, 27) = 125.91
Model | 688740.054 3 229580.018 Prob > F = 0.0000
Residual | 49229.365 27 1823.30981 R-squared = 0.9333
-------------+------------------------------ Adj R-squared = 0.9259
Total | 737969.419 30 24598.9806 Root MSE = 42.7
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y | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x1 | .001325 .000831 1.59 0.122 -.00038 .00303
x2 | .0030942 .0056214 0.55 0.587 -.0084399 .0146283
x3 | .0379664 .0072886 5.21 0.000 .0230113 .0529214
_cons | -24.28471 16.25754 -1.49 0.147 -57.64241 9.073003
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