Hi there,
I was confusing about the interpretation of the ANOVA of Multiple Linear Regression. I have done two regression and the only difference between these two is one of the variables - 'LnLGV'. For one of them, I used only LGV cars, and for the other one, I used all diesel cars. And I got two ANOVA as followed. The first one is using all diesel cars, and the second one is using LGV cars.
I think that using all diesel cars might be better since it contains all the data. However, my friend argues that the ANOVA shows the standard error of ln(HGV) is 35%, higher than 9% using only LGV cars. She thinks that the volatility is too high to produce reliable results and said the second is better.
But I think both these two model has high R square, and the coefficients are all significant at 95% level, do we have to pursue a lower standard error and higher R square? Does it make sense to compare the value?
Any of your advice would be much appreciated!
I was confusing about the interpretation of the ANOVA of Multiple Linear Regression. I have done two regression and the only difference between these two is one of the variables - 'LnLGV'. For one of them, I used only LGV cars, and for the other one, I used all diesel cars. And I got two ANOVA as followed. The first one is using all diesel cars, and the second one is using LGV cars.
I think that using all diesel cars might be better since it contains all the data. However, my friend argues that the ANOVA shows the standard error of ln(HGV) is 35%, higher than 9% using only LGV cars. She thinks that the volatility is too high to produce reliable results and said the second is better.
But I think both these two model has high R square, and the coefficients are all significant at 95% level, do we have to pursue a lower standard error and higher R square? Does it make sense to compare the value?
Any of your advice would be much appreciated!