Please see attached document
1) Use the following data to calculate the MAPD of the forecasts.
| Period | Demand | Forecasts |
| 256 | -- | |
| 270 | 245 | |
| 248 | 245 | |
| 265 | 256 | |
| 244 | 243 |
Keep two decimal places in your calculations.
| Period | AbsolutePercentage Errors |
| -- | |
Calculate the mean absolute percentage deviation (MAPD) of the forecasts?
2)
The following is the data for the number of complains a telephone company received during the past 5 weeks for the service they offer. Use the data to forecast the number of complaints for week 6, based on the following methods:
| Week | Demand |
| 111 | |
| 100 | |
| 105 | |
| 112 | |
| 114 |
Naive approach.
Simple moving average with span of 3.
Weighted moving average with weights of 0.55, 0.25, and 0.2.
Simple exponential smoothing with smoothing factor of 0.4.
Keep two decimal places in your calculations.
| Week | Forecast: Naïve | Forecast: Simple Moving Average | Forecast: Weighted Moving Average | Forecast: Exponential Smoothing |
| -- | -- | -- | -- | |
| -- | -- | -- | ||
| -- | -- | -- | ||
| -- | -- | -- | ||
| -- | -- | -- | ||
3) Use the following data to calculate the MAD and MSE of the forecasts.
| Period | Demand | Forecasts |
| 256 | -- | |
| 270 | 258 | |
| 248 | 254 | |
| 265 | 251 | |
| 244 | 259 |
| Period | Absolute Error |
| -- | |
Calculate the mean absolute deviation (MAD) of the forecasts?
Calculate the mean squared errors (MSE) of the forecasts?
4) Consider the following data. We want to monitor the forecasts.
| Period | Demand | Forecasts |
| 274 | -- | |
| 261 | 274 | |
| 294 | 261 | |
| 294 | 294 | |
| 307 | 294 |
Calculate the UCL and LCL for the appropriate control chart to control magnitude of errors?
Calculate the cumulative error, MAD, and tracking signals of periods 2 through 5 and determine if the forecasts are biased.
Keep two decimal places in your calculations .
| Period | Errors | Cumulative Errors | MADs | Tracking Signals |
| -- | -- | -- | -- | |
| ... | ... | ... | ||
| ... | ... | |||
| ... | ||||
| ... |
5) Top of Form
Are forecast errors biased? (Yes/No)
5) Consider the following data. We want to monitor the forecasts.
| Period | Demand | Forecasts |
| 276 | -- | |
| 247 | 276 | |
| 297 | 247 | |
| 284 | 297 | |
| 310 | 284 |
Calculate the UCL and LCL for the appropriate control chart to control magnitude of errors?
overall MSE:
UCL? LCL?
Are forecast errors in control?
6) Develop a linear trend equation for the following data. Then use the equation to predict the demand of period 7 and 8.
| Period | Demand | |
|
| 122 | |
|
| 140 | |
|
| 140 | |
|
| 144 | |
|
| 134 | |
|
| 152 | |
| Sum | 21 | 832 |
Sum of (Period Squared):
Sum of (Period*Demand)
Intercept?
Slope?
Forecast of period 7? 8?
