Consider the football data in Table B.1, found within Appendix B of the textbook.

Construct the overdetermined matrix equation for the multiple linear regression.

What are the sizes of each matrix? Fit a multiple linear regression model relating

the number of games won to the team's passing yardage (x2), the percentage of

rushing plays (x7), and the opponents' yards rushing (x8). Which variable explains

the most variance in the dependent variable?

If two variables are correlated, does the variance explained by both variables

separately add to the variance explained by the model at large? What situations

could arise in practical work where this might be an issue?