Consider the following gasoline time series data. Click on the webfile logo to reference the data. DATA file Sales (1000
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Consider the following gasoline time series data. Click on the webfile logo to reference the data. DATA file Sales (1000
Consider the following gasoline time series data. Click on the webfile logo to reference the data. DATA file Sales (1000s of gallons) Week 1 17 2 21 19 23 18 16 20 18 22 10 20 11 15 12 22 Show the exponential smoothing forecasts using a = 0.1 and a = 0.2 a. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a = 0.1 or α = 0.2 for the gasoline sales time series? Calculate the MSE for each smoothing constant (to 2 decimals). MSE for a = 0.1 X MSE for a = 0.2 a = 0.2 would be preferred based upon MSE. b. Are the results the same if you apply MAE as the measure of accuracy? Calculate the MAE (in 1000s of gallons) for each smoothing constant (to 2 decimals). MAE for a 0.1 MAE for a = 0.2 ✓ a = 0.1 would be preferred based upon MAE. c. What are the results if MAPE is used (to 2 decimals)? X% MAPE for a = 0.1 9.65 MAPE for = 0.2 7.41 % a = 0.1 # would be preferred based upon MAPE. 3 4 5 6 7 8 9
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