In: Statistics and Probability
|
For the attached data set, 1. create a 3-month and 6-month moving average forecast. 2. Calculate the standard errors 3. compare their forecast accuracy |
| Month/Year | Unemployment rate |
| Jan-17 | 5.1 |
| Feb-17 | 4.9 |
| Mar-17 | 4.6 |
| Apr-17 | 4.1 |
| May-17 | 4.1 |
| Jun-17 | 4.5 |
| Jul-17 | 4.6 |
| Aug-17 | 4.5 |
| Sep-17 | 4.1 |
| Oct-17 | 3.9 |
| Nov-17 | 3.9 |
| Dec-17 | 3.9 |
| Jan-18 | 4.5 |
| Feb-18 | 4.4 |
| Mar-18 | 4.1 |
| Apr-18 | 3.7 |
| May-18 | 3.6 |
| Jun-18 | 4.2 |
| Jul-18 | 4.1 |
| Aug-18 | 3.9 |
| Sep-18 | 3.6 |
| Oct-18 | 3.5 |
| Nov-18 | 3.5 |
I had done this using MINITAB as follows-
Stat- Time series -moving average . This gives output as follows-


From above standard error for
3 - month Moving Average is 0.16 and 6 - month moving average is
0.08902.
Forecast for 6 month moving average is accurate. Because it's standard error is minimum.