The Following Computer Printout Estimated Overhead Costs Using Multiple Regression

The following computer printout estimated overhead costs using multiple regression: $$\begin{array} { l c c c c } \text { Parameter } & \text { Estimate } & \begin{array} { c } \text { tfor H(0) } \\\text { Interameter } = \mathbf { 0 }\end{array} & \underline { \mathbf { P r } > \mathbf { t } } & \begin{array} { c } \text { Std. error } \\\text { of parameter }\end{array} \\\text { Intercept } & 1000 & 1.96 & 0.0250 & 510.204 \\\text { Setup hours } & 25 & 81.96 & 0.0001 & 0.305 \\\text { \# of parts } & 100 & 9.50 & 0.0001 & 10.527\end{array}$$

$\begin{array}{ll}\text { R Square (R2) } & 0.94 \\\text { Standard Error (Se) } & 75.00 \\\text { Observations } & 160\end{array}$
During the year the company used 1,000 setup hours and 500 parts.
The model being measured is

A) Overhead = 1,000 + 25(Setup hours) + 100(# of parts)
B) Overhead = 510 + 0.305(Setup hours) + 10.527(# of parts)
C) Overhead = 0.98 + 40.98(Setup hours) + 4.865(# of parts)
D) Overhead = 1,000 + 25(Setup hours)