A C D K SUMMARY OUTPUT Regression Statistics Multiple F 0.99831 5 R Square 0.99662 6 Adjusted F 0.99563 7 Standard | 82899 81 Observati 23 9 10 ANOVA 11 Edf SS MS Fanificance F 12 Regression 5 344703 68940.6 1003 17 2.2E-20 13 Residual 17 1168.28 68.7224 14 Total 22 345871 15 16 Coefficientsandard Em tStat P-value Lower 95% Upper 95%ower 95.09/pper 95.0% 17 Intercept 977.495 229.796 4.25374 0.00054 492.667 1462.32 492.667 1462.32 18 Cars 10.095 0.98122 10.2882 1E-08 8.02479 12.1652 8.02479 12.1652 19 MPG -36.6334 14.1502 -2.58889 0.01911 -66.4877 -6.77906 -66.4877 -6.77906 20 GasP 0.31735 0.66464 0.47747 0.63911 -1.08492 1.71962 -1.08492 171962 21 Reallnc -0.08377 0.03652 -2.29407 0.0348 -0.16082 -0.00673 -0.16082 -0.00673 22 LaborF -5.26324 3.0933 -1.70149 0.10707 -11.7895 1.26306 -11.7895 1.26306 23 24 25 26 Discuss the coefficients and the goodness of fit for 27 this model. Make sure to 28 discuss the implications of the sign of each 29 coefficient (positive or negative) and whether 30 or not they make economic sense. 31 32