If model A has lower MSE (mean squared error) than model B does, A is better, right?
not necessarily, since you have a sample, not population, as your training set, which means your models don't have a complete picture.
Now what do we do?
Use ANOVA (analysis of variance).
"When given a single argument it produces a table which tests whether the model terms are significant.
When given a sequence of objects, anova tests the models against one another in the order specified."
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