Random company decides that the simple regression analysis could be extended to a multiple regression analysis. He finds the following results for two multiple regression analyses Regression 4: PDC = a + (bx No. of POs) + (b2x No. of Ss) Variable Constant Independent variable 1: No. of PO. Independent variable 2: No. of $s = 0.64, Durbin-Watson statistic = 1.91 Coefficient 5484,522 $126.66 $ 2,903 Standard Error $256,684 5 57.80 5 1.459 -Value 189 2.19 1.99 Regression 5: PDC = a + (b1 * No. of POs) + (62 * No. of Ss) + (6 MPS) Variable Constant Independent variable 1: No. of POs Independent variable 2. No. of Ss Independent variable 3: MPS p=0.64Durbin-Watson statistic = 1.91 Coefficient S483.560 $ 126,58 $ 2,901 0.00002 Standard Error $312,554 $ 63.75 S 1,622 0.0029 t-Value 1.35 1.99 1.79 0.01 R4 Write the cost equation/function/formula in accounting terminology How do you determine if each of the independent variables is a cost driver? R5 Write the cost equation/function/formula in accounting terminology -How do you determine if each of the independent variables is a cost driver Would you recommend that the company use Regression 5 to predict future costs