Simple Linear Regression Bret's Accounting & Tax Services is a small accounting firm in Sioux City, IA which completes taxes for individuals. Every year, firms like Bret's decide how much they will charge to complete and file an individual tax return. This price determines how many tax returns firms complete each year. Suppose you are an office manager for a firm like Bret's Accounting and Tax Services and you are trying to determine what your firm should charge next year for tax returns. Use the following data to answer these questions. a) Graph the data using a scatter plot. Using the "Insert Trendline" function in Excel, determine whether you should use linear regression or log-linear. Insert the graph below. Be sure to label both axes. We should use regression. b) Using Excel's Regression Analysis Function, run a regression and answer the following questions about your output. i) What is your estimated demand function? ii) Discuss the fit and significance of the regression. R = of the variation in Returns Completed is explained by our regression using Return Price. The model statistically significant. c) How many returns do you expect to be completed if the firms charges $85 per return? What is the elasticity at this point in the demand curve? Are you on the elastic, inelastic, or unit elastic portion of your demand curve? Can you make a recommendation to increase or decrease price with this information? Price (P) = $85.00 Estimated Returns Completed (Q) = Own Price Elasticity = We are portion of the demand curve. The recommendation is price. d) Suppose the firm has a cost function for individual tax returns of TC = 5000 + 10Q. Using functions and Excel's Solver functionality, determine how much the firms should be charging for a return to maximize profit and the corresponding total revenue, total cost, and profit. TC = 5000 10 Q Price (P) = Estimated Returns Completed (() = Total Revenue (TR) = Total Cost (TC) = Profit =