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.
Which slope and intercept parameters are significant at the 0.05 level?
A)intercept
B)setup hours
C)number of parts
D)all of the above

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.
Which slope and intercept parameters are significant at the 0.05 level?
A)intercept
B)setup hours
C)number of parts
D)all of the above

Quizplus · Accepted Answer

All parameters (intercept, setup hours, and number of parts) are significant at the 0.05 level because their p-values are less than 0.05.

The Following Computer Printout Estimated Overhead Costs Using Multiple Regression