(CIMA, adapted) Catherine McCarthy, sales manager of Baxter Arenas, is checking to see if there is any relationship between promotional costs and ticket rev- enues at the sports stadium. She obtains the following data for the past 9 months: Promotional Costs $52,000 65,000 80,000 Month Ticket Revenues April May June $200,000 270,000 320,000 480,000 July August September 90,000 100,000 110,000 430,000 450,000 October 540,000 120,000 November 670,000 180,000 197,000 December 751,000 She estimates the following regression equation: Ticket revenues = $65,583 + ($3.54 x Promotional costs)
(CIMA, adapted) Catherine McCarthy, sales manager of Baxter Arenas, is checking to see if there is any relationship between promotional costs and ticket rev- enues at the sports stadium. She obtains the following data for the past 9 months: Promotional Costs $52,000 65,000 80,000 Month Ticket Revenues April May June $200,000 270,000 320,000 480,000 July August September 90,000 100,000 110,000 430,000 450,000 October 540,000 120,000 November 670,000 180,000 197,000 December 751,000 She estimates the following regression equation: Ticket revenues = $65,583 + ($3.54 x Promotional costs)
Chapter1: Financial Statements And Business Decisions
Section: Chapter Questions
Problem 1Q
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Using (a) the regression equation and (b) the high-low equation, what is the increase in revenues for each $10,000 spent on promotional costs within the relevant range? Which method should Catherine use to predict the effect of promotional costs on ticket revenues? Explain briefly.
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