Susan Garrard, sales manager of Becker Arenas, is checking to see if there is any relationship between promotional costs and ticket revenues at the sports stadium. She obtains the following data for the past 9 months:

She estimates the following regression equation:

Ticket revenues = $ 39 comma 502 + ($ 3.40 x Promotional costs)

1. Draw the regression line and evaluate it using the criteria of economic plausibility, goodness of fit, and slope of the regression line.

2. Draw the regression line and evaluate it using the criteria of economic plausibility, goodness of fit, and slope of the regression line.

3. Use the high-low method to compute the function relating promotional costs and revenues.

Using (a) the regression equation and (b) the high-low equation, what is the increase in revenues for each $10,000 spent on promotional within the relevant range? Which method should Susan use to predict the effect of promotional costs on revenues? Explain briefly.

Begin by plotting the regression line using April and December's advertising cost levels, then round the monthly revenues to the nearest increment of $100. (Enlarge the graph and use the line button displayed below to draw the graph.)

Month	Ticket Revenues			Promotional Costs
April		$220,000			$51,000
May		290,000			64,000
June		340,000			79,000
July		500,000			89,000
August		450,000			99,000
September		470,000			109,000
October		560,000			119,000
November		690,000			179,000
December		785,500			196,000

She estimates the following regression equation:

Ticket revenues =

$ 39,502 + $ 3.40 x Promotional costs)