The following time series shows the number of units of a particular product sold over the past six months.
Month |
Units Sold |
1 |
9 |
2 |
4 |
3 |
5 |
4 |
6 |
5 |
13 |
6 |
11 |
a. Compute the three-month moving average forecast for month 4.
b. Compute the three-month moving average forecast for month 5.
c. Compute the three-month moving average forecast for month 6.
d. Compute the mean squared error (MSE) for the three-month moving average forecasts.
e. Use α = 0.3 to compute the exponential smoothing forecast for month 2.
f. Use α = 0.3 to compute the exponential smoothing forecast for month 3.
g. Use α = 0.3 to compute the exponential smoothing forecast for month 4.
h. Use α = 0.3 to compute the exponential smoothing forecast for month 5.
i. Use α = 0.3 to compute the exponential smoothing forecast for month 6.
j. Compute the mean absolute percentage error (MAPE) for the exponential smoothing forecasts.
k. Use α = 0.3 to compute the exponential smoothing forecast for month 7.
a,b,c,d
period | demand | forcast | forecast error=demand value-forecast value | absolute forecast error | squared forcast error |
t | Dt | Ft | et=Dt-Ft | | et | | (et)² |
1 | 9 | ||||
2 | 4 | ||||
3 | 5 | ||||
4 | 6 | 6.000 | 0.00 | 0.00 | 0.00 |
5 | 13 | 5.000 | 8.00 | 8.00 | 64.00 |
6 | 11 | 8.000 | 3.00 | 3.00 | 9.00 |
MSE= Σ(et)²/n = 24.33
e)
Month | Sales ($1000) |
Forecast ŷt+1 = yt*α + ŷt*(1-α) |
1 | 9 | 9 |
2 | 4 | 9.00 |
3 | 5 | 7.50 |
4 | 6 | 6.75 |
5 | 13 | 6.53 |
6 | 11 | 8.47 |
7 | 9.23 |
period | demand | forcast | forecast error=demand value-forecast value | absolute forecast error | squared forcast error |
t | Dt | Ft | et=Dt-Ft | | et | | (et)² |
1 | |||||
2 | 4 | 9.000 | -5.00 | 5.00 | 25.00 |
3 | 5 | 7.500 | -2.50 | 2.50 | 6.25 |
4 | 6 | 6.750 | -0.75 | 0.75 | 0.56 |
5 | 13 | 6.525 | 6.48 | 6.48 | 41.93 |
6 | 11 | 8.468 | 2.53 | 2.53 | 6.41 |
MSE= Σ(et)²/n = 16.03
THANKS
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