Source | SS df MS Number of obs = 950 -------------+----------------------------
ID: 3310610 • Letter: S
Question
Source | SS df MS Number of obs = 950
-------------+---------------------------------- F(2, 947) = 447.02
Model | 4.7894e+11 2 2.3947e+11 Prob > F = 0.0000
Residual | 5.0731e+11 947 535703444 R-squared = 0.4856
-------------+---------------------------------- Adj R-squared = 0.4845
Total | 9.8625e+11 949 1.0393e+09 Root MSE = 23145
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SHW | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
THI | .101915 .0034374 29.65 0.000 .0951692 .1086608
NFM | -86.72231 315.8477 -0.27 0.784 -706.5646 533.12
_cons | 6321.588 1734.366 3.64 0.000 2917.944 9725.232
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Interpret the results
Explanation / Answer
From the given results, we can have a look at the p-value computed for each of the independent variable, the p-value is very very low for the intercept that is _cons and for THI but the p-value for the variable NFM is 0.784 > 0.05 which is the level of significance generally taken in case of regression analysis. This shows that the variables THI and _cons here are significant but the variable NFM is insignificant.
This can also be seen from the 95% confidence interval computed for each of the independent variable. The confidence interval for NFM contains 0 which indicates that at 5% level of significance, the independent variable NFM is insignificant and therefore should not be there in the model.
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