Including irrelevant independent variables into the model:
A) Will create bias
B) Will reduce the precision of our estimates.
C) Will have no negative or positive effect
D) Will lead to an increase in the error term.

Question

Quizplus · Accepted Answer

Including irrelevant independent variables into the model will reduce the precision of our estimates. This is because including irrelevant variables in the model increases the number of parameters, and thus decreases the degrees of freedom, which can reduce the precision of our estimates.

Including Irrelevant Independent Variables into the Model