Period NRURF (%) INC ($ Billions) SF1 Mar-17 7.6 1.928 Jun-17 7.7 1,972 Sep-17 7.5 2,017 Dec-17 7.4 2,062 c. Actual sales for 2017 were: Q1 = 334.271; Q2 = 328,982; Q3 = 317,921; Q4 = 350,118. On the basis of this information, how well would you say the model worked? What is the mean absolute percentage error (MAPE)? f. Plot the actual data for 2017Q1 through 201704 along with the values predicted for each quarter based on this model.\f(I. Now you can expand your analysis to see whether a multipleregression model would work well. Estimate the following model: SALES .50 + L}. [INC] + bgtNRUR) SALES : _ + f _(INC} + f _[NRUR) {Circle + or as appropriate for each variable} Do the signs on the coefficients make sense? Explain why. b. Test to see whether the coefficients you have estimated are statistically different from zero. using a 95 percent confidence level and a one-tailed test. c. What percentage of the variation in sales is explained by this model'? (2'. Use this model to make a sales forecast ($131} for 2017Q] through 2017Q4. given the previously forecast values for unemployment (NRU'RF) and income (WCF) as follows