Case study
ksmth0
forcastingTemplate-1.xlsx4 mth moving average
| Forecasting | Moving averages - 4 period moving average | ||||||
| Num pds | 4 | ||||||
| Data Elissa Torres: Forecasting: Submodel = 11; Problem size @ 11 by 4 | Forecasts and Error Analysis | ||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | |
| Period 1 | |||||||
| Period 2 | |||||||
| Period 3 | |||||||
| Period 4 | |||||||
| Period 5 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 6 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 7 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 8 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 9 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 10 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Period 11 | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ||
| Total | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |||
| Average | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | ERROR:#DIV/0! | |||
| Bias | MAD | MSE | MAPE | ||||
| SE | ERROR:#DIV/0! | ||||||
| Next period | ERROR:#DIV/0! | Not enough data to compute the standard error |
Forecasting
Demand Forecast 0 0 0 0 0 0 0Time
Value
Enter the past demands in the data area
Weighted Moving Average
| Forecasting | Weighted moving averages - 2 period moving average | |||||||
| Data Elissa Torres: Forecasting: Submodel = 12; Problem size @ 11 by 2 | Forecasts and Error Analysis | |||||||
| Period | Demand | Weights | Forecast | Error | Absolute | Squared | Abs Pct Err | |
| Period 1 | 0.15 | |||||||
| Period 2 | 0.3 | |||||||
| Period 3 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 4 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 5 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 6 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 7 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 8 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 9 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 10 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Period 11 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Total | 0 | 0 | 0 | ERROR:#DIV/0! | ||||
| Average | 0 | 0 | 0 | ERROR:#DIV/0! | ||||
| Bias | MAD | MSE | MAPE | |||||
| SE | 0 | |||||||
| Next period | 0 |
Forecasting
Demand Forecast 0 0 0 0 0 0 0 0 0Time
Value
Enter the data in the shaded area. Enter weights in INCREASING order from top to bottom.
Exponential Smoothing
| Forecasting | Exponential smoothing | ||||||
| Alpha | 0.05 | ||||||
| Data Elissa Torres: Forecasting: Submodel = 13; Problem size @ 11 by 1 | Forecasts and Error Analysis | ||||||
| Period | Demand | Forecast | Error | Absolute | Squared | Abs Pct Err | |
| Period 1 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 2 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 3 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 4 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 5 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 6 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 7 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 8 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 9 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 10 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Period 11 | 0 | 0 | 0 | 0 | ERROR:#DIV/0! | ||
| Total | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Average | 0 | 0 | 0 | ERROR:#DIV/0! | |||
| Bias | MAD | MSE | MAPE | ||||
| SE | 0 | ||||||
| Next period | 0 |
Forecasting
0 0 0 0 0 0 0 0 0 0 0Time
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.
