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 + (bix No. of POs) + (b2x No. of Ss) Value Variable Constant Independent variable 1. No. of PO. Independent variable 2. No. of $s = 0.64, Durbin-Watson statistic = 1.91 Coefficient $484,522 $126.66 $ 2,903 Standard Error $256,684 $ 57.80 $ 1,459 189 2.19 1.99 Regression 5: PDC = a + (by * No. of POs) + (b2 x No. of Ss) + (6 MPS) -Value Variable Constant Independent variable 1: No. of POs Independent variable 2. No. of Ss Independent variable 3: MPS p = 0,64: Durbin-Watson statistic = 1.91 Coefficient S483,560 $ 126,58 $ 2,901 0.00002 Standard Error $312,554 $ 63.75 $ 1,622 0.0029 1.55 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