Bus Planning
Summary
2 period moving average
| Forecasting | Moving averages - 2 period moving average | |||||||
| Num pds | 3 | |||||||
| Data Elissa Torres: Forecasting: Submodel = 11; Problem size @ 5 by 3 | Forecasts and Error Analysis | |||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||
| Period 1 | 38 | |||||||
| Period 2 | 40 | |||||||
| Period 3 | 41 | 39 | 2 | 2 | 4 | 04.88% | ||
| Period 4 | 37 | 40.5 | -3.5 | 3.5 | 12.25 | 09.46% | ||
| Period 5 | 45 | 39 | 6 | 6 | 36 | 13.33% | ||
| Total | 4.5 | 11.5 | 52.25 | 27.67% | ||||
| Average | 1.5 | 3.8333333333 | 17.4166666667 | 09.22% | before forecast | |||
| Bias | MAD | MSE | MAPE | |||||
| Period 6 | 50 | 47.5 | 2.5 | 2.5 | 6.25 | 05.00% | ||
| Period 7 | 44 | Average | after forecast period 6 | |||||
| Bias | MAD | MSE | MAPE |
Forecasting
Demand 38 40 41 37 45 Forecast 39 40.5 39Time
Value
Enter the past demands in the data area
3 period moving average
| Forecasting | Moving averages - 3 period moving average | |||||||
| Num pds | 3 | |||||||
| Data Elissa Torres: Forecasting: Submodel = 11; Problem size @ 5 by 3 | Forecasts and Error Analysis | |||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||
| Period 1 | 38 | |||||||
| Period 2 | 40 | |||||||
| Period 3 | 41 | |||||||
| Period 4 | 37 | 39.6666666667 | -2.6666666667 | 2.6666666667 | 7.1111111111 | 07.21% | ||
| Period 5 | 45 | 39.3333333333 | 5.6666666667 | 5.6666666667 | 32.1111111111 | 12.59% | ||
| Total | 3 | 8.3333333333 | 39.2222222222 | 19.80% | ||||
| Average | 1.5 | 4.1666666667 | 19.6111111111 | 09.90% | ||||
| Bias | MAD | MSE | MAPE | |||||
| Period 6 | 50 | 44 | 6 | 6 | 36 | 12.00% | ||
| Period 7 | 44 | Average | after forecast period 6 | |||||
| Bias | MAD | MSE | MAPE |
Forecasting
Demand 38 40 41 37 45 Forecast 39.666666 666666664 39.333333333333336Time
Value
Enter the past demands in the data area
Exponential Smoothing
| Forecasting | Exponential smoothing | |||||||
| Alpha | 0.3 | |||||||
| Data Elissa Torres: Forecasting: Submodel = 13; Problem size @ 5 by 1 | Forecasts and Error Analysis | |||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | ||
| Period 1 | 38 | 38 | 0 | 0 | 0 | 0.00% | ||
| Period 2 | 40 | 38 | 2 | 2 | 4 | 5.00% | ||
| Period 3 | 41 | 38.6 | 2.4 | 2.4 | 5.76 | 5.85% | ||
| Period 4 | 37 | 39.32 | -2.32 | 2.32 | 5.3824 | 6.27% | ||
| Period 5 | 45 | 38.624 | 6.376 | 6.376 | 40.653376 | 14.17% | ||
| Total | 8.456 | 13.096 | 55.795776 | 31.29% | ||||
| Average | 1.6912 | 2.6192 | 11.1591552 | 06.26% | Before forecast | |||
| Bias | MAD | MSE | MAPE | |||||
| SE | 4.3126084914 | |||||||
| Period 6 | 50 | 40.5368 | 9.4632 | 9.4632 | 89.55215424 | 18.93% | ||
| Period 7 | 44 | Average | after forecast period 6 | |||||
| Bias | MAD | MSE | MAPE |
Forecasting
38 40 41 37 45 38 38 38.6 39.32 38.624000000000002Time
Value
Enter alpha (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. If the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.
Trend Adj Exp Smoothing
| Forecasting | Trend adjusted exponential smoothing | |||||||||
| Alpha | 0.3 | |||||||||
| Beta | 0.7 | |||||||||
| Data Elissa Torres: Forecasting: Submodel = 14; Problem size @ 5 by 1 | Forecasts and Error Analysis | |||||||||
| Period | Demand | Smoothed Forecast, Ft | Smoothed Trend, Tt | Forecast Including Trend, FITt | Error | Absolute | Squared | Abs Pct Err | ||
| Period 1 | 38 | 38 | 38 | 0 | 0 | 0 | 00.00% | |||
| Period 2 | 40 | 38 | 0 | 38 | 2 | 2 | 4 | 05.00% | ||
| Period 3 | 41 | 38.6 | 0.42 | 39.02 | 1.98 | 1.98 | 3.9204 | 04.83% | ||
| Period 4 | 37 | 39.614 | 0.8358 | 40.4498 | -3.4498 | 3.4498 | 11.90112004 | 09.32% | ||
| Period 5 | 45 | 39.41486 | 0.111342 | 39.526202 | 5.473798 | 5.473798 | 29.9624645448 | 0.1216399556 | ||
| Next period | 41.1683414 | 1.26083958 | 42.42918098 | |||||||
| Total | 6.003998 | 12.903598 | 49.7839845848 | 31.32% | ||||||
| 41.1683414 | Average | 1.2007996 | 2.5807196 | 9.956796917 | 06.26% | |||||
| Bias | MAD | MSE | MAPE | |||||||
| SE | 4.0736545666 | |||||||||
| Next period | 42.050929106 | 0.6178113942 | 42.6687405002 | |||||||
| Total | After forecast | |||||||||
| Average | ||||||||||
| Bias | MAD | MSE | MAPE | |||||||
| SE | 0 |
Forecasting
Demand 38 40 41 37 45 Smoothed Forecast, Ft 38 38 38.599999999999994 39.61399999999999 39.41485999999999Time
Value
Enter alpha and beta (between 0 and 1), enter the past demands in the shaded column then enter a starting forecast. If the starting forecast is not in the first period then delete the error analysis for all rows above the starting forecast.