The Saskatoon Company manufactures motorcycles. The company's management accountant wants to calculate the fixed and variable costs associated with utility cost incurred by the factory. Data for the past five months were collected. $\begin{array}{lrr}& \text { Utility } & \text { Machine } \\text { Month } &\text { cost }&\text { hours }\
\text { March } & \$ 30,255 & 2,200 \
\text { April } & 32,750 & 2,525 \
\text { May } & 34,712 & 2,710 \
\text { June } & 31,850 & 2,410 \
\text { July } & 30,720 & 2,290
\end{array}$
-Refer to the Figure.When using a linear regression program,what is the forecasted utility cost at 4,000 machine hours (rounded to the nearest dollar)?
A)$10,631
B)$28,288
C)$37,116
D)$45,945

Question

Quizplus · Accepted Answer

To forecast the utility cost at 4,000 machine hours using linear regression, we first need to determine the linear relationship between utility costs and machine hours. Linear regression will give us an equation of the form $y = mx + b$, where $y$ is the utility cost, $x$ is the machine hours, $m$ is the slope of the line (variable cost per machine hour), and $b$ is the y-intercept (fixed cost). Although the exact slope and intercept are not provided, the question implies using a linear regression program to determine these values based on the provided data. Once the linear equation is determined, we can substitute $x = 4,000$ machine hours into the equation to forecast the utility cost. The correct answer (D) $45,945 suggests that after performing the linear regression analysis and applying the 4,000 machine hours into the derived equation, the forecasted utility cost rounds to this amount. This process involves statistical analysis which is not explicitly shown here, but the answer is derived from applying linear regression to the given data points.

The Saskatoon Company Manufactures Motorcycles -Refer to the Figure