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D Question 1 1.6 pts Open the winev10 JMP file and and see that it has yearly wine consumption data in millions of liters. Perform

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D Question 1 1.6 pts Open the winev10 JMP file and and see that it has yearly wine consumption data in millions of liters. Perform (1) naive forecasting: (2) simple average forecasting: (3) moving average forecasting of order 3; and (4) exponential smoothing forecasting using alpha=0.8 and the forecast value for Year 2001 - 1.915. Complete the following statements: V 1. The naive forecast for Year 2013 is 2.673 2. The simple average forecast for Year 2013 is 2.275 3. The moving average forecast of order 3 for Year 2013 is 2.522 4. The exponential smoothing forecast using alpha=0.8 for Year 2013 is [Select 5. The cumulative forecast error for the naive forecasting method is Select) 6. The mean absolute percentage error for the exponential smoothing forecasting method is Select > 7. Using cumulative forecast error as the forecasting metric, naive forecasting is the best method in this case (T/F) T 8. Using mean absolute percentage error as the forecasting metric, exponential smoothing forecasting is the best method in this case (T/F) F D Question 1 1.6 pts Open the winev10 JMP file and and see that it has yearly wine consumption data in millions of liters. Perform (1) naive forecasting: (2) simple average forecasting: (3) moving average forecasting of order 3; and (4) exponential smoothing forecasting using alpha=0.8 and the forecast value for Year 2001 - 1.915. Complete the following statements: V 1. The naive forecast for Year 2013 is 2.673 2. The simple average forecast for Year 2013 is 2.275 3. The moving average forecast of order 3 for Year 2013 is 2.522 4. The exponential smoothing forecast using alpha=0.8 for Year 2013 is [Select 5. The cumulative forecast error for the naive forecasting method is Select) 6. The mean absolute percentage error for the exponential smoothing forecasting method is Select > 7. Using cumulative forecast error as the forecasting metric, naive forecasting is the best method in this case (T/F) T 8. Using mean absolute percentage error as the forecasting metric, exponential smoothing forecasting is the best method in this case (T/F) F

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