The following table shows the square errors, (Y - Y). for forecasts from 2005 through 2009. Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Moving Average Exponential Smoothing (5-year) (3-year) (W = 0.9) (W = 0.3) Year 2005 9,025 3,249 784 7,569 2006 6,400 2,209 529 6,561 2007 4,225 1,369 289 5,184 2008 2,500 729 144 3,600 2009 1,225 289 36 2,209 RMSE

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The following table shows the square errors,
(Y-P). for forecasts from 2005 through 2009.
Fill the table by calculating the root mean square error (RMSE) for each of the methods.
Square Error
Moving Average
Exponential Smoothing
(5-year)
(3-year)
(W = 0.9)
(W = 0.3)
Year
2005
9,025
3,249
784
7,569
2006
6,400
2,209
529
6,561
2007
4,225
1,369
289
5,184
2008
2,500
729
144
3,600
2009
1,225
289
36
2,209
RMSE
Based on the RMSE criterion, which of the forecasting methods is the most accurate?
Exponential smoothing (w = 0.9)
O Three-year moving average
Exponential smoothing (w- 0.3)
O Five-year moving average
Transcribed Image Text:The following table shows the square errors, (Y-P). for forecasts from 2005 through 2009. Fill the table by calculating the root mean square error (RMSE) for each of the methods. Square Error Moving Average Exponential Smoothing (5-year) (3-year) (W = 0.9) (W = 0.3) Year 2005 9,025 3,249 784 7,569 2006 6,400 2,209 529 6,561 2007 4,225 1,369 289 5,184 2008 2,500 729 144 3,600 2009 1,225 289 36 2,209 RMSE Based on the RMSE criterion, which of the forecasting methods is the most accurate? Exponential smoothing (w = 0.9) O Three-year moving average Exponential smoothing (w- 0.3) O Five-year moving average
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