Consider the following time series data.
Week | 1 | 2 | 3 | 4 | 5 | 6 |
Value | 18 | 14 | 16 | 10 | 19 | 13 |
Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.
(a) | Mean absolute error |
If required, round your answer to one decimal place. | |
(b) | Mean squared error |
If required, round your answer to one decimal place. | |
(c) | Mean absolute percentage error |
If required, round your intermediate calculations and final answer to two decimal places. | |
(d) | What is the forecast for week 7? |
Time period | Actual Value(A) | Moving avg. Forecast(F) | Forecast error E=|A-F| | Squared Forecast Error | |A-F|A |
1 | 18 | ||||
2 | 14 | 18 | 4 | 16 | 0.2857 |
3 | 16 | 14 | 2 | 4 | 0.1250 |
4 | 10 | 16 | 6 | 36 | 0.6000 |
5 | 19 | 10 | 9 | 81 | 0.4737 |
6 | 13 | 19 | 6 | 36 | 0.4615 |
7 | 13 | ||||
Total | 27 | 173 | 1.95 | ||
Average | 5.40 | 34.60 | 38.92% | ||
MAD | MSE | MAPE | |||
a) mean absolute error= | 5.4 | ||||
b) mean squared error = | 34.6 | ||||
c) mean absolute % error= | 38.92% | ||||
d) forecast for week 7 = | 13 |
Get Answers For Free
Most questions answered within 1 hours.