Consider the following time series data.
Week | 1 | 2 | 3 | 4 | 5 | 6 |
Value | 20 | 12 | 16 | 10 | 18 | 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 | 20 | ||||
2 | 12 | 20 | 8 | 64 | 0.6667 |
3 | 16 | 12 | 4 | 16 | 0.2500 |
4 | 10 | 16 | 6 | 36 | 0.6000 |
5 | 18 | 10 | 8 | 64 | 0.4444 |
6 | 13 | 18 | 5 | 25 | 0.3846 |
7 | 13 | ||||
Total | 31 | 205 | 2.35 | ||
Average | 6.20 | 41.00 | 46.91% | ||
MAD | MSE | MAPE |
a)
Mean absolute error =6.20
b)
Mean squared error = | 41.00 |
c)
Mean absolute percentage error = | 46.91% |
d)
forecast for week 7 =13
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