In multiple regression, one's goal should be to effectively explain the variation in the dependent variable by using as many independent variables as possible.

Question

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Adding too many independent variables can lead to overfitting, where the model becomes too complex and performs well on the training data but poorly on new, unseen data. The goal is to explain the variation in the dependent variable with a model that is as simple as possible while still being effective, adhering to the principle of parsimony.

In Multiple Regression, One's Goal Should Be to Effectively Explain