Exercise 17.09} Consider the following gasoline time series data. Click on the d
ID: 3319593 • Letter: E
Question
Exercise 17.09}
Consider the following gasoline time series data.
Click on the datafile logo to reference the data.
show the exponential smoothing forecasts using = 0.1.
Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of = .1 or = .2 for the gasoline sales time series (to 2 decimals)?
alpha equal to .2 provides more accurate forecasts based upon MSESelectalpha equal to .1 provides more accurate forecasts based upon MSEalpha equal to .2 provides more accurate forecasts based upon MSE
Are the results the same if you apply MAE as the measure of accuracy (to 2 decimals)?
alpha equal to .1 provides more accurate forecasts based upon MAESelectalpha equal to .1 provides more accurate forecasts based upon MAEalpha equal to .2 provides more accurate forecasts based upon MAE
What are the results if MAPE is used (to 2 decimals)?
alpha equal to .1 provides more accurate forecasts based upon MAPESelectalpha equal to .1 provides more accurate forecasts based upon MAPEalpha equal to .2 provides more accurate forecasts based upon MAPE
Explanation / Answer
with 0.1 alpha:
with 0.2 alpha:
more accurate forecasts based upon MSE =19.18
more accurate forecasts based upon MSE =18.64
more accurate forecasts based upon MSE =18.64
week sales(A) Forecast(F) (A-F)^2 |A-F| |A-F|/A 1 17 2 21 17.00 16.00 4.00 0.19 3 19 17.40 2.56 1.60 0.08 4 23 17.56 29.59 5.44 0.24 5 18 18.10 0.01 0.10 0.01 6 16 18.09 4.38 2.09 0.13 7 20 17.88 4.48 2.12 0.11 8 18 18.10 0.01 0.10 0.01 9 22 18.09 15.32 3.91 0.18 10 20 18.48 2.32 1.52 0.08 11 15 18.63 13.18 3.63 0.24 12 22 18.27 13.94 3.73 0.17 18.64 total 101.78 28.25 1.42 average 9.25 2.57 12.95% MSE MAE MAPERelated Questions
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