Marketing: In the field of marketing, a propensity to convert model is used to predict the likelihood for a customer to accept your company's offer. This model can be used for direct mail campaigns where the cost of marketing is high, for example. In this case, you only want to send the offers to customers with a high propensity to convert. The following data have been obtained by the Leeds Marketing Firm for a client. The data are available in the worksheet entitled "Marketing" A simple linear regression model was fit to predict the propensity to convert (PROPENSITY as a percent) from age in years (AGE). The model equation is given here: Propensity = 10.716 - 0.037Age (a) Fit a curvilinear model by regressing the propensity to convert (PROPENSITY) on the reciprocal of age. Note: AgeINV referenced below is a variable that you will create. (Enter your answers to three decimal places.) Propensity = (blank) + (blank)AgeINV (b) Summary measures for the linear model appear below. Provide summary measures for the transformed model. IMPORTANT: Note that R7 needs to be entered as a PERCENT (Enter only the number in the answer box, not the symbol). (Enter your answers to three decimal places.) Model: Linear Model R^2 6.660 % Se 1.040 Reciprocal Model R^2 (blank)% Se (blank) (c) Which is the better fitting model? Justify your choice