The Following Computer Printout Estimated Overhead Costs Using Multiple Regression

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


$\begin{array}{lc}\text { R Square }\left(\mathrm{R}^{2}\right) & 0.94 \\\text { Standard Error }\left(\mathrm{S}_{\mathrm{e}}\right) & 75.00 \\\text { Observations } & 160\end{array}$
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) .