Table 10.9
$$\begin{array} { | c | c | c | }
\hline \text { Quarter } & \begin{array} { c }
\text { Forecasted } \
\text { Demand } \
\text { (Units) }
\end{array} & \begin{array} { c }
\text { Actual } \
\text { Demand } \
\text { (Units) }
\end{array} \
\hline 1 & 85 & 95 \
2 & 55 & 55 \
3 & 70 & 45 \
4 & 60 & 75 \
\hline
\end{array}$$
-Use the information in Table 10.9.What is the standard deviation of forecast errors for the data?
A) 0 units
B) greater than 0, but less than or equal to 10 units
C) greater than 10, but less than 20 units
D) greater than 20 units

Question

Table 10.9
 $$\begin{array} { | c | c | c | } 
\hline \text { Quarter } & \begin{array} { c } 
\text { Forecasted } \
\text { Demand } \
\text { (Units) }
\end{array} & \begin{array} { c } 
\text { Actual } \
\text { Demand } \
\text { (Units) }
\end{array} \
\hline 1 & 85 & 95 \
2 & 55 & 55 \
3 & 70 & 45 \
4 & 60 & 75 \
\hline
\end{array}$$
-Use the information in Table 10.9.What is the standard deviation of forecast errors for the data?
A) 0 units
B) greater than 0, but less than or equal to 10 units
C) greater than 10, but less than 20 units
D) greater than 20 units

Quizplus · Accepted Answer

To find the standard deviation of forecast errors, we need to calculate the difference between the actual demand and the forecasted demand for each quarter, and then calculate the standard deviation of those differences. The differences for each quarter are:

Q1: 95-85=10
Q2: 55-55=0
Q3: 45-70=-25
Q4: 75-60=15

The average of these differences is (10+0-25+15)/4=0. Therefore, the standard deviation is:

sqrt[( (10-0)^2 + (0-0)^2 + (-25-0)^2 + (15-0)^2 )/4] = sqrt [650/4] = 12.76

Thus, the standard deviation of forecast errors is greater than 10, but less than 20 units, so the answer is C.

Table 109 -Use the Information in Table 10