ABC Industries wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis showed the following information (note: only a portion of the regression analysis results is presented here): Regression Statistics Multiple R .991108748 R Square .982296551 Adjusted R Square 977870689 Standard Error 67.58593536 Observations 6 Anova DF SS Regression Residual Total 1 4 5 1013811.899 18271.43463 1032083.333 MS F 1013811.899 221.9446735 4567.656659 Intercept X Variable 1 COEFFICIENT STANDARD ERROR ESTAT P-value 2945.94652 194.105844 15.1701095 .000108885 .718590832.04823467 14.89780767 .00011823 Using the cost equation from this regression analysis, and an "x" of 7,712, what would total predicted costs be? Hint: Before calculating your final answer, round fixed costs and variable costs to FOUR decimal places. (FOR EXAMPLE: .857632 ROUNDS TO.8576. FOR EXAMPLE 3945.45689 ROUNDS TO 3945.4569) Then, round your final answer to two decimal places. (FOR EXAMPLE 4569.1568 ROUNDS TO 4569.16)