Refer again to the gasoline sales time series data in the following table. Using
ID: 370823 • Letter: R
Question
Refer again to the gasoline sales time series data in the following table.
Using a weight of 1/2 for the most recent observation, 1/3 for the second most recent, and 1/6 for third most recent, compute a three-week weighted moving average for the time series. Use rounded for two decimal places values for intermediate colculations.
Compute the MSE for the weighted moving average in part a. Do you prefer this weighted moving average to the unweighted moving average? Remember that the MSE for the unweighted moving average is 10.22. Round your answer to two decimal places.
MSE =
Prefer the moving average here.
Suppose you are allowed to choose any weights as long as they sum to 1. Could you always find a set of weights that would make the MSE smaller for a weighted moving average than for an unweighted moving average? Why or why not?
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Week Sales (1000s of gallons) 1 16 2 21 3 19 4 26 5 19 6 17 7 22 8 16 9 24 10 23 11 16 12 24Explanation / Answer
MSE = Sum of Error square/(n-1)
MSE = 197.72/(9-1) = 24.72
No, this weighted moving average is not prefered as MSE value is higher
Yes, It is always wise to chose the weights or forecasting method which gives minimum MSE. Higher the value of MSE, more is the likely hood of error
Week Sales Forecast (F) Error (D-F) Error Sq 1 16 2 21 3 19 4 26 19.17 6.83 46.69 5 19 22.83 (3.83) 14.69 6 17 21.33 (4.33) 18.78 7 22 19.17 2.83 8.03 8 16 19.83 (3.83) 14.69 9 24 18.17 5.83 34.03 10 23 21.00 2.00 4.00 11 16 22.17 (6.17) 38.03 12 24 19.67 4.33 18.78 78 243 183.33 3.67 197.72Related Questions
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