I am confused regarding how to calculate the formula for MSE (mean squared error) in a forecast. I was taught that the formula is SSE/n-p-1 (with n being the number of observations and p the number of independent variables).
I was assigned a homework problem and used the MSE from the ANOVA table that Excel generated for a regression. It was four years of sales data and we had to use Excel to do a regression with dummy variables for the seasonality.
When the professor went over it, he indicated that technically it should have been just "n" in the denominator, but he would accept "n-p-1". He also indicated that other statistics software would have calculated the MSE using the technically correct "n" in the denominator.
I just don't understand the whole n versus n-p-1 issue and when it is appropriate to use one or the other. As most material I see uses n-p-1, I know it has to be right sometimes? And Excel generates it based on that?
I hoped that made some sense.
Any help would GREATLY be appreciated and help relieve a statistics induced headache.
Thank You,
Tim
I was assigned a homework problem and used the MSE from the ANOVA table that Excel generated for a regression. It was four years of sales data and we had to use Excel to do a regression with dummy variables for the seasonality.
When the professor went over it, he indicated that technically it should have been just "n" in the denominator, but he would accept "n-p-1". He also indicated that other statistics software would have calculated the MSE using the technically correct "n" in the denominator.
I just don't understand the whole n versus n-p-1 issue and when it is appropriate to use one or the other. As most material I see uses n-p-1, I know it has to be right sometimes? And Excel generates it based on that?
I hoped that made some sense.
Any help would GREATLY be appreciated and help relieve a statistics induced headache.
Thank You,
Tim