With the gasoline time series data from the given table, show the exponential smoothing forecasts using = 0.1.

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With the gasoline time series data from the given table, show the exponential smoothing forecasts using a = 0.1. Week Sales (1000s of gallons) 1 17 21 2 3 19 4 23 5 18 6 16 7 20 8 18 22 9 10 20 11 15 12 22 a. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a = 0.1 or a = 0.2 for the gasoline sales time series? Do not round your interim computations and round your final answers to two decimal places. a = 0.1 = 0.2 MSE Prefer: b. Are the results the same if you apply MAE as the measure accuracy? Do not round your interim computations and round your final answers to two decimal places. C = 0.1 Ox = 0.2 8 18 9 22 10 20 11 15 12 22 smoothing constant of a = 0.1 or ax = 0.2 for the gasoline sales time series? Do not round your interim computations and round your final a. Applying the MSE measure of forecast accuracy, would you prefer answers to two decimal places. cx = 0.1 cx = 0.2 MSE Prefer: b. Are the result: 0.1 me if you apply MAE as the measure of accuracy? Do not round your interim computations and round your final answers to two decimal places. 0.2 0.1 x = 0.2 MAE Prefer: C. What are the results if MAPE is used? Do not round your interim computations and round your final answers to two decimal places. a = 0.1 a = 0.2 MAPE % Prefer