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.