Homework Sourse1 Actual demands for the last four months are as follows Wha
1. Actual demands for the last four months are as follows.
What is the forecast value (model generated value) for May and June using exponential smoothing with Alpha = 0.2? Assume actual and forecast values for March are same. Show work.
2. While monitoring the forecast values based on simple moving average method (averaging period = 3), the tracking signals are consistently coming out as large positive numbers (i.e., 4.0, 6.2, and 5.5). What should we do to the forecast model?
3. Given the actual data on the left, what is the forecast for period 6, using a four-period weighted moving average with weights of .1, .2, .3 and .4 (greater weight towards more recent time)?
4. Use exponential smoothing technique. With alpha = 0.1. Assume forecast value for week 1 is same as actual value for week 1. Fill out below table.
week
demand
forecast
1
430
430
2
289
3
367
4
470
5
468
6
365
5. The Freewheel motorcycle dealer in the Chicago area wants to be able to forecast accurately the demand for the Freewheel Super Z12 motorcycle. From sales records, the dealer has accumulated the following data for the second half of 2015.
Month Sales
July 10
August 15
September 23
October 44
November 54
December 36
Compute a 4-month moving average forecast of demand for January 2016.
6. Moving Average with different averaging periods:
Year
Actual
Sales
Forecast
AP=1
ABS(Error)
Forecast
AP=2
ABS(Error)
Forecast
AP=4
ABS(Error)
1
565
2
590
3
583
4
597
5
615
597
18
590
25
583.75
31.25
6
611
615
4
606
5
596.25
14.75
7
610
611
1
613
3
601.5
8.5
8
623
610
13
610.5
12.5
608.25
14.75
Sum:
36
45.5
69.25
Which Moving Average model is most accurate based on MAD?
| week | demand | forecast |
| 1 | 430 | 430 |
| 2 | 289 | |
| 3 | 367 | |
| 4 | 470 | |
| 5 | 468 | |
| 6 | 365 |
Solution
1. Actual demands for the last four months are as follows.
What is the forecast value (model generated value) for May and June using exponential smoothing with Alpha = 0.2? Assume actual and forecast values for March are same. Show work.
Answer: F = (1-0.2)(70)+0.2(60) = 68
if actual demand = 60
and forecasted demand = 70
2. While monitoring the forecast values based on simple moving average method (averaging period = 3), the tracking signals are consistently coming out as large positive numbers (i.e., 4.0, 6.2, and 5.5). What should we do to the forecast model?
Answer: we shoulf use smoothing technique to deal with this problem.
3. Given the actual data on the left, what is the forecast for period 6, using a four-period weighted moving average with weights of .1, .2, .3 and .4 (greater weight towards more recent time)?
Answer: the weights can be used to find the forecasted data.
4. Use exponential smoothing technique. With alpha = 0.1. Assume forecast value for week 1 is same as actual value for week 1. Fill out below table.
week
demand
forecast
1
430
430
2
289
289
3
367
367
4
470
470
5
468
468
6
365
365
5. The Freewheel motorcycle dealer in the Chicago area wants to be able to forecast accurately the demand for the Freewheel Super Z12 motorcycle. From sales records, the dealer has accumulated the following data for the second half of 2015.
Month Sales
July 10
August 15
September 23
October 44
November 54
December 36
Compute a 4-month moving average forecast of demand for January 2016.
6. Moving Average with different averaging periods:
Year
Actual
Sales
Forecast
AP=1
ABS(Error)
Forecast
AP=2
ABS(Error)
Forecast
AP=4
ABS(Error)
1
565
2
590
3
583
4
597
5
615
597
18
590
25
583.75
31.25
6
611
615
4
606
5
596.25
14.75
7
610
611
1
613
3
601.5
8.5
8
623
610
13
610.5
12.5
608.25
14.75
Sum:
36
45.5
69.25
Which Moving Average model is most accurate based on MAD?
Answer: AP-4
| week | demand | forecast |
| 1 | 430 | 430 |
| 2 | 289 | 289 |
| 3 | 367 | 367 |
| 4 | 470 | 470 |
| 5 | 468 | 468 |
| 6 | 365 | 365 |
