Consider the accompanying time series.
a. Forecast the demand for each quarter in Year 4 using multiplicative decomposition.
b. Interpret the meaning of the seasonal components.
c. Calculate the MAD for this forecast.
Year_1_Quarter Year_ 1_Demand
Year_2_Quarter Year_2_Demand
Year_3_Quarter Year_3_Demand
1 4 1 5 1 8
2 10 2 13 2 16
3 11 3 11 3 14
4 5 4 9 4 8
.
The MINITAB output is:
Method
Model type | Multiplicative Model |
Data | Demand |
Length | 12 |
NMissing | 0 |
Fitted Trend Equation
Yt = 5.46 + 0.593×t |
Seasonal Indices
Period | Index |
1 | 0.67690 |
2 | 1.47660 |
3 | 1.33477 |
4 | 0.51174 |
Accuracy Measures
MAPE | 12.2786 |
MAD | 0.9778 |
MSD | 1.3145 |
Forecasts
Period | Forecast |
13 | 8.9099 |
14 | 20.3116 |
15 | 19.1519 |
16 | 7.6460 |
a. Forecast the demand for each quarter in Year 4 using multiplicative decomposition.
Forecasts
Period | Forecast |
13 | 8.9099 |
14 | 20.3116 |
15 | 19.1519 |
16 | 7.6460 |
b. Interpret the meaning of the seasonal components.
Quarter 2 has the highest demand, followed by Quarter 3, followed by Quarter 1 and then by Quarter 4.
c. Calculate the MAD for this forecast.
MAD | 0.9778 |
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