Comparing nested models using F test

Hi all, I want to compare two models to see if they are significantly different.

Total number of obs = 981

Model 1: y = b0 + b1x1 + b2x2 + b3x2
Model 2: y = b0 + b1x1 + b2x2 .... + b5x5

How do I compare the two regressions? Is using the difference in F-values for both models, with df1 = 2, and df2 = 975 (981-6)?
It depends what type of regression you are running. Since these are not nested, they have different variables, AIC is probably your best bet. There are chi square tests I believe for analyzing if models are better, but they have to be nested.

This would be a nested model

y=b0 +b1X1 + b2X2

compared to

y=b0 + b1X1

one is a subset of the other.


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We might want to determine if they are nested or not. Seems more likely that they just made a typo on that first model.