Consider the following time series data. Week 1 2 3 4 5 6
Value 19 13 16 11 18 14
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 | 19 | ||||
2 | 13 | 19 | 6 | 36 | 0.4615 |
3 | 16 | 13 | 3 | 9 | 0.1875 |
4 | 11 | 16 | 5 | 25 | 0.4545 |
5 | 18 | 11 | 7 | 49 | 0.3889 |
6 | 14 | 18 | 4 | 16 | 0.2857 |
7 | 14 | ||||
Total | 25 | 135 | 1.78 | ||
Average | 5.00 | 27.00 | 35.56% | ||
MAD | MSE | MAPE |
a)
Mean absolute error =5.0
b)
Mean squared error=27.0
c)
Mean absolute percentage error =35.56%
d)
forecast for week 7 =14
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