Demand for a product and the forecasting department's forecast (naïve model) for a product are shown below. Compute the mean squared error. ?
? $$\begin{array} { | c | c | c | }
\hline \text { Period } & \text { Actual Demand } & \text { Forecasted Demand } \
\hline 1 & 12 & - \
\hline 2 & 15 & 12 \
\hline 3 & 14 & 15 \
\hline 4 & 18 & 16 \
\hline
\end{array}$$
A)3.33
B)4.67
C)5.33
D)6.67

Question

Demand for a product and the forecasting department's forecast (naïve model) for a product are shown below. Compute the mean squared error. ?
? $$\begin{array} { | c | c | c | } 
\hline \text { Period } & \text { Actual Demand } & \text { Forecasted Demand } \
\hline 1 & 12 & - \
\hline 2 & 15 & 12 \
\hline 3 & 14 & 15 \
\hline 4 & 18 & 16 \
\hline
\end{array}$$
A)3.33
B)4.67
C)5.33
D)6.67

Quizplus · Accepted Answer

The mean squared error (MSE) is calculated by taking the average of the squared differences between actual and forecasted values. Here, the squared differences are (15-12)² = 9, (14-15)² = 1, and (18-16)² = 4. The MSE is (9+1+4)/3 = 4.67.

Demand for a Product and the Forecasting Department's Forecast (Naïve