Consider the following gasoline sales time series. If needed, round your answers

Question

Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits Week Sales (1,000s of gallons) 17 21 16 2 4 17 18 7 8 9 10 20 21 19 16 25 12 (a) Show the exponential smoothing forecasts using a 0.1, and a0.2 Exponential Smoothing Week 0.1 0.2 13 (b) 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 An - Select your answersmoothing constant provides the more accurate forecast, with an overall MSE of (c) Are the results the same if you apply MAE as the measure of accuracy? An-select your answer-vl smoothing constant provides the more accurate forecast, with an overall MAE of (d) What are the results if MAPE is used? - Select your answer - a = 0.1 An smoothing constant provides the more accurate forecast, with an overall MAPE of -0.2

Explanation / Answer

for 0.1 level ;

for alpha =0.2;

a)

b)

an alpha=0.2 smoothing constant .........with an overal MSE of 12.19

an alpha=0.2 smoothing constant .........with an overal MAE of 2.83

an alpha=0.1 smoothing constant .........with an overal MAPE of 13.34% (please try 0.13 if found wrong)

week sales(A) forecast(F) |A-F| (A-F)^2 |A-F|/A 1 17 2 21 17.00 4.00 16.00 0.19 3 16 17.40 1.40 1.96 0.09 4 24 17.26 6.74 45.43 0.28 5 17 17.93 0.93 0.87 0.05 6 18 17.84 0.16 0.03 0.01 7 22 17.86 4.14 17.17 0.19 8 20 18.27 1.73 2.99 0.09 9 21 18.44 2.56 6.53 0.12 10 19 18.70 0.30 0.09 0.02 11 16 18.73 2.73 7.45 0.17 12 25 18.46 6.54 42.82 0.26 19.11 total 31.24 141.34 1.47 average 2.84 12.85 13.34% MAD MSE MAPE

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