What does it mean to validate a regression model?
Correct Answer
B) Testing how it performs on data not used to fit it
Why this is correct: Model validation tests whether a regression model generalizes beyond the specific data used to create it. This is done by applying the model to a new, independent set of data (a holdout sample or later time period) and checking the accuracy of its predictions. Why the other choices are wrong: Confirming arithmetic is part of checking, not validation. Verifying every sale is data cleaning. Checking that R-squared exceeds a threshold measures fit on the original data, not predictive power on new data. Exam tip: A high R-squared on your training data doesn't guarantee a good model. Always validate with out-of-sample data to check for overfitting.
Why This Is the Correct Answer
Why this is correct: Model validation tests whether a regression model generalizes beyond the specific data used to create it. This is done by applying the model to a new, independent set of data (a holdout sample or later time period) and checking the accuracy of its predictions. Why the other choices are wrong: Confirming arithmetic is part of checking, not validation. Verifying every sale is data cleaning. Checking that R-squared exceeds a threshold measures fit on the original data, not predictive power on new data. Exam tip: A high R-squared on your training data doesn't guarantee a good model. Always validate with out-of-sample data to check for overfitting.
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