MAT 540 Quantiative Methods Strayer wk4 hmk
P2
| Carpet City | ||||
| Month | Demand for Soft Shag Carpet (1,000 yd.) | 3 mos moving average forecast | Weighted 3 mos moving average forecast | |
| 1 | 8 | |||
| 2 | 12 | |||
| 3 | 7 | |||
| 4 | 9 | |||
| 5 | 15 | |||
| 6 | 11 | |||
| 7 | 10 | |||
| 8 | 12 | |||
| 9 | ||||
| Please apply weights stated in the problem | ||||
| Compute MAD on 3 mos moving average | ||||
| Compute MAD on weighted 3 mos moving average | ||||
| Which is a better forecast method? |
P6
| Petroco Service Station | ||||
| alpha = | 0.3 | |||
| Month | Gas Demand | Exp Forecast | Error | |
| October | 800 | |||
| November | 725 | 777.5 | ||
| December | 630 | |||
| January | 500 | |||
| February | 645 | |||
| March | 690 | |||
| April | 730 | |||
| May | 810 | |||
| June | 1200 | |||
| July | 980 | |||
| 7710 | ||||
| 0.00 | SUM | |||
| MAPD | ||||
| 0.00% |
P9
| Science and Technology Mutual Fund | ||||||
| alpha = | 0.4 | |||||
| Month | Fund Price | 3 mos moving average forecast | Weighted 3 mos moving average forecast | Exp Forecast | ||
| 1 | 63 1/4 | |||||
| 2 | 60 1/8 | |||||
| 3 | 61 3/4 | |||||
| 4 | 64 1/4 | |||||
| 5 | 59 3/8 | |||||
| 6 | 57 7/8 | |||||
| 7 | 62 1/4 | |||||
| 8 | 65 1/8 | |||||
| 9 | 68 1/4 | |||||
| 10 | 65 1/2 | |||||
| 11 | 68 1/8 | |||||
| 12 | 63 1/4 | |||||
| 13 | 64 3/8 | |||||
| 14 | 68 5/8 | |||||
| 15 | 70 1/8 | |||||
| 16 | 72 3/4 | |||||
| 17 | 74 1/8 | |||||
| 18 | 71 3/4 | |||||
| 19 | 75 1/2 | |||||
| 20 | 76 3/4 | |||||
| 21 | ||||||
| Please apply weights stated in the problem | ||||||
| Compute MAD on 3 mos moving average | ||||||
| Compute MAD on weighted 3 mos moving average | ||||||
| Compute MAD on exponentially smoothed forecast | ||||||
| Which is a better forecast method? |
P26
| Carpet City Regression | |||||
| Monthly Carpet Sales (1,000 yd.) | Monthly Construction Permits | ||||
| 5 | 21 | ||||
| 10 | 35 | ||||
| 4 | 10 | ||||
| 3 | 12 | ||||
| 8 | 16 | ||||
| 2 | 9 | If 30 construction permits issued | |||
| 12 | 41 | What is expected carpet sales (1000 yds)? | |||
| 11 | 15 | ||||
| 9 | 18 | ||||
| 14 | 26 | Correlation Coefficient | |||
| Place regression output here |
P27 and P28
| Gilley's Ice Cream Parlor | |||||
| x | y | ||||
| Ave. Temp | Ice cream Sold | ||||
| Week | (degrees) | (gal.) | |||
| 1 | 73 | 110 | |||
| 2 | 65 | 95 | |||
| 3 | 81 | 135 | |||
| 4 | 90 | 160 | If average 85 deg weekly daytime temperature | ||
| 5 | 75 | 97 | What is expected ice cream sold? | ||
| 6 | 77 | 105 | |||
| 7 | 82 | 120 | Correlation Coefficient | ||
| 8 | 93 | 175 | |||
| 9 | 86 | 140 | Coefficient of Determination | ||
| 10 | 79 | 121 | |||
| Place regression output here | |||||