Consider the following time series with forecast values and errors.
$$\begin{array} { | l | l | }
\hline \begin{array} { l }
\text { Actual } \
\text { Demand }
\end{array} & \begin{array} { l }
\text { Forecast } \
\text { Demand }
\end{array} \
\hline 10 & 9 \
\hline 13 & 15 \
\hline 15 & 16 \
\hline 11 & 13 \
\hline 12 & 10 \
\hline
\end{array}$$
-Calculate the mean square deviation (MSD).
A)2.8
B)13.4
C)7.5
D)1.6
E)2.4

Question

Consider the following time series with forecast values and errors.
$$\begin{array} { | l | l | } 
\hline \begin{array} { l } 
\text { Actual } \
\text { Demand }
\end{array} & \begin{array} { l } 
\text { Forecast } \
\text { Demand }
\end{array} \
\hline 10 & 9 \
\hline 13 & 15 \
\hline 15 & 16 \
\hline 11 & 13 \
\hline 12 & 10 \
\hline
\end{array}$$
-Calculate the mean square deviation (MSD).
A)2.8
B)13.4
C)7.5
D)1.6
E)2.4

Quizplus · Accepted Answer

The mean square deviation (MSD) is calculated by taking the square of each error (actual demand - forecast demand), summing these squares, and then dividing by the number of observations. The errors are: 1 (10-9), -2 (13-15), -1 (15-16), -2 (11-13), and 2 (12-10). Squaring these gives: 1, 4, 1, 4, and 4. Summing these squares gives 14. Dividing by the number of observations (5) gives an MSD of 2.8.

Consider the Following Time Series with Forecast Values and Errors