Question

Study Prep, Chapter 13: Correlation, Simple Linear Regression, Multiple Regression MULTIPLE REGRESSION Major League Baseball Team (Team) recently hired Trixie, a third year student in the Fowler College of Business, for an internship position. After showing Trixie around the facilities, Team provided Trixie with an office, desk, computer, phone, and instructed her to "figure out what professional baseball teams need to do to get fans in the seats." Below is a regression model Trixie developed in trying to get a better understanding of the "fans in the seats" conundrum Regression Statistics 0.7824 Multiple R R Square Adj. R Square Standard Error Observations 30.0000 Alpha - .05 ANOVA df MS 1322.8668 7.5735 Sig. F Regression Residual Total 5.0000 6614.3340 24.0000 4192.1157 29.0000 10806.4497 0.0002 174.6715 Strd. Error Lower 95% P- Upper 95% Coefficients 7.7974 1.4949 0.3125 -0.0090 0.7316 0.1928 63.8217 2.6136 1.0130 0.0876 0.0928 0.9269-15.544917.0081 0.3848 Intercept AVE TIX WINS RUNS PLAYOFF PAYROLL 27.1449 0.5420 0.3394 0.0468 7.8863 0.0726 0.2872 0.7764 -48.2270 0.3762 -0.3881 -0.1057 2.7579 0.0109 0.9206 0.3664 -0.1933 0.8484 ??? 0.0113 -0.0392 5. What variable in the Regression Statistics table is the best measure of the true strength of variables and the Y-variable? 6. Is more of the variation in PCT/CAP explained by chance or the predictor variables? 7. If a team's average ticket price is $27, they won 87 games last season, scored 750 runs last the relationship between the x- season, did not make the playoffs, and their payroll is $120 million, approximately what is their predicted PCT/CAP? 8. What variables are not good predictors? 9. What team was the biggest over-performer? 10. What team was the biggest under-performer? 11. What two variables suffer the most frommulticollinearity? 12. Which of the predictor(s) is a dummy variable?

Answer 1

5)
t for Payroll = 0.1928/0.0726 = 2.65564

we see that highest magnitude of TS is of independent variable AVE TIX (2.7579)

hence AVE TIX is the best measure of true strength of the relationship

6)
R^2 = 0.7824^2 = 0.6121
since   0.6121 > 0.5
more of variation is explained by predictor variables

7)

intercept	7.7974	1
AVE TIX	1.4949	27
Wins	0.3125	87
Runs	-0.009	750
Playoff	0.7316	0
Payroll	0.1928	120
	y^	91.7332

8)

WINS, RUNS AND PLAYOFF   are not good predictors