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.
What is the predicted overhead cost?
A)$2,500
B)$75,000
C)$76,000
D)none of these

Question

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.
What is the predicted overhead cost?
A)$2,500
B)$75,000
C)$76,000
D)none of these

Quizplus · Accepted Answer

The predicted overhead cost is calculated as: Intercept + (Setup hours coefficient * Setup hours) + (# of parts coefficient * # of parts) = 1000 + (25 * 1000) + (100 * 500) = 76,000.

The Following Computer Printout Estimated Overhead Costs Using Multiple Regression