Here€™s a multiple regression model for the variables considered in Exercise 12:

a) Write the regression model.
b) What does the coefficient of Paid Attendance mean in this regression? Does that make sense?
c) In a week in which the paid attendance was 200,000 customers attending 30 shows at an average ticket price of $70, what would you estimate the receipts would be?
d) Is this likely to be a good prediction? Why do you think that?

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Dependent variable is: ReceiptS(SM) R squared. 99.9% R squared (adjusted): 99.9% s 0.0931 with 74 degrees of freedom Source Regression 484.789 Residual Variable Intercept Paid Sum of Squares df Mean Square F-ratio 3 161.596 18634 0.641736 74 0.008672 Coeff SE(Coeff) t-ratio P-value -18.320 0.3127 -58 . 0. 0001 Attendance # Shows Average 0.076 0.0006 0.0070 0.0044 126.7 <0.0001 1.59 0.116 Ticket Price .24 0.0039 61.5<0.0001