7) The following results are from data that were collected from a sample of Chicago Cubs baseball games. The dependent variable is ATTENDANCE, TEMP is a variable measuring the forecasted game-time temperature: WIN% is a variable measuring the winning percentage of the Cubs before the game is played, OPWIN% is a variable measuring the winning percentage of their opponent, WEEKEND is a dummy variable = 1 if the game is played on a weekend and = 0 if the game is played during a weekday, PROMOTION is a dummy variable = 1 if there is a promotion for the game (giving away something to those who attend the game) and = 0 if there is not a promotion, and WEEK*PROM is an interaction term equal to WEEKEND*PROMOTION. What is the predicted attendance if TEMP = 70, WIN% = 500, OPWIN% = 500, the game is played on a weekday and there is NO promotion? e) What is the predicted attendance if TEMP = 70, WIN% = 500, OPWIN% = 500, the game is played on a weekday and there is a promotion? f) Based on your answers to the previous 2 questions, what is the marginal impact of offering a promotion for weekday games? g) Based on your answers to c) and f), if you were in charge of deciding when promotion should be offered, would you suggest that you have a promotion on a weekend or a weekday? Explain.
Extracted text: 7) The following results are from data that were collected from a sample of Chicago Cubs baseball games. The dependent variable is ATTENDANCE, TEMP is a variable measuring the forecasted game time temperature: WIN% is a variable measuring the winning percentage of the Cubs before the game is played, OPWIN% is a variable measuring the winning percentage of their opponent, WEEKEND is a dummy variable 1 if the game is played on a weekend and 0 if the game is played during a weekday, PROMOTION is a dummy variable = 1 if there is a promotion for the game (giving away something to those who attend the game) and = 0 if there is not a promotion, and WEEK*PROM is an interaction term equal to WEEKEND*PROMOTION. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.639 0.408 0.360 Standard Error 4289 Observations 81 ANOVA df 6. SS MS Significance F 0.00000051 Regression 937187572 156197929 8.49 Residual 74 1361494231 18398571 Total 80 2298681803 Coefficients Standard Error t Stat P-value Upper 95% 24536.7 Lower 95% Intercept Temp 12405.7 6088.2 2.04 0.05 274.8 72.6 38.9 1.87 0.07 -4.8 150.1 Win% 24.3 12.4 1.97 0.05 -0.3 49.0 OpWin% 5.7 6.0 0.94 0.35 -6.3 17.6 Weekend 5254.6 1654.8 3.18 0.00 1957.2 8551.9 Promotion 4432.5 1363.6 3.25 0.00 1715.5 7149.5 Week*Prom -3057.6 1830.5 -1.67 0.10 -6700.3 585.1 a) What is the predicted attendance if TEMP = 70, WIN% = 500, OPWIN% = 500, the game is played on a weekend and there is NO promotion?