Ticket prices, part 2.

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 ($M) R squared = 99.9% R squared (adjusted) = 99.9% s = 0.0931 with 74 degrees of freedom Sum of Squares df Mean Square F-ratio Source Regression 484.7891 3 161.596 18634 Residual 0.641736 74 0.008672 Variable Intercept Coeff -18.320 SE (Coeff) t-ratio P-value 0.3127 -58.6 <0.0001 Paid Attendance # Shows 0.076 0.0006 0.0070 0.0044 126.7 <0.0001 1.59 0.116 Average Ticket Price 0.24 0.0039 61.5 <0.0001