1. A company has the following demand for the previous nine weeks. Use the information to develop
a. a four-period simple moving average and a forecast for period 10.
b. develop a four-period weighted moving average using the weights 0.4, 0.3, 0.2, and 0.1
c. develop a single exponential forecast for period 10 using a smoothing constant, α, equal to 0.25. Use 403 as the initial forecast.
|
Period
|
Actual Demand: At
|
|
1
|
403
|
|
2
|
422
|
|
3
|
325
|
|
4
|
428
|
|
5
|
332
|
|
6
|
317
|
|
7
|
376
|
|
8
|
478
|
|
9
|
382
|
2. The Washington Company has the following actual and forecast values for its primary product. Compute the mean absolute deviation (MAD), the mean squared error (MSE), the bias, and the mean average percent error (MAPE).
|
Period
|
At
|
Ft
|
|
1
|
1829
|
2050
|
|
2
|
1901
|
1900
|
|
3
|
1814
|
1995
|
|
4
|
1887
|
2208
|
|
5
|
1896
|
1787
|
|
6
|
1814
|
2103
|
|
7
|
1877
|
1787
|
|
8
|
1898
|
1914
|
|
9
|
1904
|
2042
|
|
10
|
1912
|
2024
|
3. For the following 12 periods of historical data, compute a simple linear regression equation and develop a forecast for the next four periods.
|
Period (x)
|
Demand (y)
|
|
1
|
108
|
|
2
|
112
|
|
3
|
107
|
|
4
|
118
|
|
5
|
131
|
|
6
|
126
|
|
7
|
138
|
|
8
|
145
|
|
9
|
159
|
|
10
|
138
|
|
11
|
153
|
|
12
|
159
|
4. Quarterly data for the most recent three years of a product's demand is shown below. Use the data to develop a forecast for periods 13 through 16 using multiplicative seasonal model (Seasonal Variation in data). Plot both desasonalized and re-seasonalized forecast data for period 1 through 16 and comment your observation.
|
X
|
Y
|
|
1
|
575
|
|
2
|
590
|
|
3
|
610
|
|
4
|
485
|
|
5
|
605
|
|
6
|
638
|
|
7
|
691
|
|
8
|
538
|
|
9
|
666
|
|
10
|
680
|
|
11
|
695
|
|
12
|
555
|