A good regression model has the fewest number of explanatory variables providing an adequate interpretation of the dependent variable.

Question

Quizplus · Accepted Answer

A model that includes too many explanatory variables can lead to overfitting, which means it may work well on the specific data used to build the model but may not generalize well to new data. Therefore, it is generally preferable to choose a model with the fewest number of variables that still accurately captures the relationship between the dependent and independent variables.

A Good Regression Model Has the Fewest Number of Explanatory