SUMMARY OUTPUT 18. Based on the simple regression results below, identify the cost estimation model. Regression Statistics Multiple R R Square 0.9667903 0.934683483 Adjusted R Square 0.930841335 Standard Error Observations ANOVA Regression Residual Total 15.30989452 19 df SS MS F Significance F 1 17 57021.00542 57021.01 243.2711 1.66384E-11 3984.678795 234.3929 18 61005.68421 Upper Lower Upper Coefficients Standard Error t Stat P-value Lower 95% 95% 95.0% 95.0% Intercept 1.969640788 X Variable 1 9.14919993 0.21528 0.832111 7.922711472 0.507958934 15.59715 1.66E-11 17.33348375 21.27277 6.851011799 8.994411 -17.3335 21.27277 6.851012 8.994411 (Continued on next page) 7 A. TC 9.15 +7.92*X B. TC 1.97 +7.92*X C. TC 17.33 + 1.97*X D. TC7.92 + 1.97*X