Question

3 multiple choice 1 point what does it suggest if the adjusted r² is substantially smaller than r²? the model is overfitting the data the model contains useless predictors the model contains useful predictors the model is highly predictive

Explanation:

The adjusted $R^{2}$ adjusts for the number of predictors in the model. When it is much smaller than the $R^{2}$, it implies that some of the predictors may not be contributing significantly to the model's explanatory power, i.e., they are useless predictors. $R^{2}$ always increases or stays the same when adding predictors, while adjusted $R^{2}$ only increases if the new predictor improves the model enough to offset the penalty for adding a predictor.

Answer:

The model contains useless predictors