Business math?
5) The follow table lists the demand of cakes during the past few months. Use the data to forecast the demand for May, based on the following methods:
| Month | Demand |
| Jan | 100 |
| Feb | 96 |
| Mar | 90 |
| Apr | 96 |
Naive approach.
Simple moving average with span of 2.
Weighted moving average with weights of 0.5, 0.38, and 0.12.
Simple exponential smoothing with smoothing factor of 0.15.
Keep two decimal places in your calculations.
| Month | Forecasts: Naïve | Forecasts: Simple Moving | Forecasts: Weighted Moving | Forecasts: Exponential |
| Jan | ||||
| Feb | ||||
| Mar | ||||
| Apr | ||||
| May |
6) Consider the following data. We want to monitor the forecasts.
| Period | Demand | Forecasts |
| 52 | -- | |
| 62 | 58 | |
| 59 | 62 | |
| 53 | 66 | |
| 58 | 68 |
Also, we want to monitor the forecasts using tracking signals with control limits of ±4 MADs.
Answer the following related questions:
Below fill in the blanks (cumulative errors, MADs, and tracking signals of periods 3, 4 and 5).
Keep two decimal places in your calculations.
| Period | Cumulate Errors | MADs | Tracking Signals |
| --- | -- | -- | |
| -- | -- | -- | |
Based on tracking signals of period 4 and 5, are the forecasts biased? (Yes/No)
7) Consider the following data. We want to monitor the forecasts.
| Period | Demand | Forecasts |
| 52 | -- | |
| 62 | 67 | |
| 59 | 67 | |
| 53 | 64 | |
| 58 | 62 |
We want to calculate the UCL and the LCL for the appropriate control chart to monitor the magnitute of errors.
Answer the following related questions:
Below fill in the blanks (errors of periods 2 through 5).
Keep two decimal places in your calculations.
| Period | Errors |
| -- | |
Calculate the overall MSE to determine if the errors of the forecasts are in control. overall MSE:
UCL for the control chart?
LCL for control Chart?
Based on your control chart, are the forecasts in control? (Yes/No)
