Sara Tomlinson, sales manager of Gullo 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: (Click the icon to view the data.) Requirement 1. Draw the regression line and evaluate it using the criteria of economic plausibility, goodness of fit, and slope of the regression line. 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.) Revenues $898,888 $800,000- $760,000- $720,000- $680,000- $640,000 $600,000 $560,000- $520,000- $480,000 $440,000 $400,000 $360,000- $320,000- $280,000- $240,000. $200,000+ $160,000- $120,000- $80,000+ $40,0005,09010, 001045, 0180$208,000 She estimates the following regression equation: Ticket revenues = $33,515+ ($4.00 Promotional costs) Read the requirements. Click to 1. Draw the regression line and evaluate it using the criteria of economic plausibility, goodness of fit, and slope of the regression line. 2. Use the high-low method to compute the function relating promotional costs and revenues. 3. 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 Sara use to predict the effect of promotional costs on revenues? Explain briefly.