Question
In: Statistics and Probability
1) Using a 5 period simple moving average, the forecast for period 13 will be:
Question 1 contains the actual values for 12 periods (listed in order, 1-12). In Excel, create forecasts for periods 6-13 using each of the following methods: 5 period simple moving average; 4 period weighted moving average (0.63, 0.26, 0.08, 0.03); exponential smoothing (alpha = 0.23 and the forecast for period 5 = 53); linear regression with the equation based on all 12 periods; and quadratic regression with the equation based on all 12 periods. Round all numerical answers to two decimal places.
The actual values for 12 periods (shown in order) are:
(1) 45 (2) 52 (3) 48 (4) 59 (5) 55 (6) 57 (7) 64 (8) 58 (9) 68 (10) 66 (11) 72 (12) 75
1) Using a 5 period simple moving average, the forecast for period 13 will be:
2) Using the 4 period weighted moving average, the forecast for period 13 will be:
3) With exponential smoothing, the forecast for period 13 will be:
4) With linear regression, the forecast for period 13 will be:
5) With quadratic regression, the forecast for period 13 will be:
6) Considering only the forecasts for period 6-12, what is the lowest MAD value for any of the methods?
Solutions
Expert Solution
As per company policies, I am answering 4 PARTS only
| D) | A) | B) | C) | ||
| T | Demand | Trend | MA(5) | WMA(4) | ES(a=0.23) |
| 1 | 45 | 46.513 | #N/A | ||
| 2 | 52 | 48.950 | 45.000 | ||
| 3 | 48 | 51.387 | 46.610 | ||
| 4 | 59 | 53.824 | 46.930 | ||
| 5 | 55 | 56.261 | 47.480 | 49.706 | |
| 6 | 57 | 58.698 | 51.800 | 51.610 | 50.924 |
| 7 | 64 | 61.135 | 54.200 | 51.690 | 52.321 |
| 8 | 58 | 63.572 | 56.600 | 57.950 | 55.007 |
| 9 | 68 | 66.009 | 58.600 | 56.330 | 55.696 |
| 10 | 66 | 68.446 | 60.400 | 59.230 | 58.526 |
| 11 | 72 | 70.883 | 62.600 | 62.820 | 60.245 |
| 12 | 75 | 73.321 | 65.600 | 61.660 | 62.948 |
| 13 | , FORECAST | 75.758 | 67.800 | 68.010 | 65.720 |
| Intercept= | 44.07576 | ||||
| Slope= | 2.437063 |
excel sheet: replace " =" by "="
| D) | A) | B) | C) | ||
| t | demand | trend | MA(5) | WMA(4) | ES(a =0.23) |
| 1 | 45 | =$D$22+$D$23*A3 | #N/A | ||
| 2 | 52 | =$D$22+$D$23*A4 | =B3 | ||
| 3 | 48 | =$D$22+$D$23*A5 | =G4+0.23*(B4-G4) | ||
| 4 | 59 | =$D$22+$D$23*A6 | =G5+0.23*(B5-G5) | ||
| 5 | 55 | =$D$22+$D$23*A7 | =0.63*B3+0.26*B4+0.08*B5+0.03*B6 | =G6+0.23*(B6-G6) | |
| 6 | 57 | =$D$22+$D$23*A8 | =AVERAGE(B3:B7) | =0.63*B4+0.26*B5+0.08*B6+0.03*B7 | =G7+0.23*(B7-G7) |
| 7 | 64 | =$D$22+$D$23*A9 | =AVERAGE(B4:B8) | =0.63*B5+0.26*B6+0.08*B7+0.03*B8 | =G8+0.23*(B8-G8) |
| 8 | 58 | =$D$22+$D$23*A10 | =AVERAGE(B5:B9) | =0.63*B6+0.26*B7+0.08*B8+0.03*B9 | =G9+0.23*(B9-G9) |
| 9 | 68 | =$D$22+$D$23*A11 | =AVERAGE(B6:B10) | =0.63*B7+0.26*B8+0.08*B9+0.03*B10 | =G10+0.23*(B10-G10) |
| 10 | 66 | =$D$22+$D$23*A12 | =AVERAGE(B7:B11) | =0.63*B8+0.26*B9+0.08*B10+0.03*B11 | =G11+0.23*(B11-G11) |
| 11 | 72 | =$D$22+$D$23*A13 | =AVERAGE(B8:B12) | =0.63*B9+0.26*B10+0.08*B11+0.03*B12 | =G12+0.23*(B12-G12) |
| 12 | 75 | =$D$22+$D$23*A14 | =AVERAGE(B9:B13) | =0.63*B10+0.26*B11+0.08*B12+0.03*B13 | =G13+0.23*(B13-G13) |
| 13 | , FORECAST | =$D$22+$D$23*A15 | =AVERAGE(B10:B14) | =0.63*B11+0.26*B12+0.08*B13+0.03*B14 | =G14+0.23*(B14-G14) |
| intercept = | =INTERCEPT(B3:B14,A3:A14) | ||||
| slope = | =SLOPE(B3:B14,A3:A14) | ||||
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