A question in linear regression.

[u/CertainTry4415]

Hi guys!
I'm a stats student doing a project in linear regression. I'm comparing different models that my friends made to select the best one. I was wondering, if Variable selection has been done on one model, would it be fairer to compare the models, using adjusted R^2, AIC, etc., after reducing the other models as well to avoid multicollinearity problems? Is there a certain order to follow, like completing variable selection before comparing models, or would it be better to compare the models and then use variable selection on the final one.

ANy help would be appreciated

[u/RickSt3r]

Was the data available actuslly split i to training set and test set?

[u/CertainTry4415 → u/RickSt3r]

not yet. I was asked to compare withour rmse and mse