An attendance demand model using multiple linear regression analysis has been used to predict game-day attendance for football games for the Division I Big 10 conference.

The regression model yielded an Adjusted R-squared of 0.76 (76%) and the beta-coefficients of the independent variables are listed below.

Independent Variable	Coefficient	P-Value
Home Population	0.002	2 x 10-9
Weekday	-0.14	0.002
Distance between the visiting team	-.03	0.03
Home points per game	0.41	0.99
Visitor points per game	0.32	0.83
The home team's previous victory	0.18	0.67
Rivalry index	0.84	3 x 10-7
Home win probability	0.25	0.0001
Uncertainty of outcome	-0.40	0.17

Q. Using the linear regression analysis output above, which among the 9 factors(independent variables) are significant predictors of game-day attendance in Big Ten college football? Which are non-significant predictors in the model?

Q. Among the significant predictors of attendance you chose above, explain the direction (interpret the sign) and magnitude (coefficient absolute value) of how each independent variable affects attendance.