qVery often, one predictor is a function of the other predictors.
qIt becomes an important question: How many predictors do we need in order to make a good
regression (or prediction)?
qDoes increasing the number of the predictor improve the regression (or prediction)?
qIf too many predictors are used, some large coefficients may be assigned to variables that are not
really highly correlated to the predictant (y). These coefficients are generated to help the regression relation to fit y.
qTo answer this question, we have to figure out how fast (or slow) the “fraction of explained
variance” increase with additional number of predictors.