In general for a fitted regression model what does adjusted

In general, for a fitted regression model, what does adjusted R-squared do that “regular” R-squared does not?

It accounts for the number of x variables in the model, giving us a penalty for including x variables that are not really useful in predicting Y.

It tells us the increase on the mean of Y for a one-unit increase in x, holding all other variables fixed.

It forces R-squared to be between -1 and 1.

It always gets larger as more x variables are added to the model, whether the variables are useful or not.

It allows us to conduct the model F test

Solution

It accounts for the number of x variables in the model, giving us a penalty for including x variables that are not really useful in predicting Y.