All the statistical data below are used to illustrate the fitting effect of the model as a whole. Among them, in general papers, most only pay attention to and explain a few indicators:
R squared 0.247783 indicates that the goodness of fit of the model is 0.247783, and the larger the value, the better. If the maximum value is 1.24, it can only be said that it is average or poor, but it is normal to get such a result by regression.
Durbin-Watson stat 1.756974 indicates that the D.W statistic is1.756974, which is used to explain whether the residual obeys normal distribution. D.W is equal to 2, which is a normal distribution, and 1.756974 is a little smaller than 2, which is ideal. It can be considered that the residual obeys normal distribution and the model is available.
F-statistical 3.767555, Prob (f-statistical) 0.000005, which means F-statistical > and its corresponding P value, is used to test the overall significance of the model, F-statistical >; 2. The probability density function < 0.05 is significant, otherwise the whole model is not significant and the model is meaningless. Your test shows that this model is meaningful as a whole.
Ordinary linear regression of other statistics needs no explanation. If you want to know more about it, I suggest reading a textbook about EVIEWS, there are many. Of course, if you want to do in-depth research, what you need is far from the mechanical operation method of statistical software. The principles of econometrics are very important. As long as you read more relevant textbooks and materials and understand the principle, it is very simple to operate the software.