103 Forecasting Gasoline 3 methods - INPUTS OUTPUTS Number of Periods in Moving Average = Number of Periods of Data Collected = 4 mean squared error 12

103 Forecasting Gasoline 3 methods - INPUTS OUTPUTS Number...

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INPUTS OUTPUTS Number of Periods in Moving Average = 4 mean squared error Number of Periods of Data Collected = 12 MSE = 9.648438 MAPE = MAD = 2.71875 LAD = OUTPUTS mean absolute deviation(error) Forecast = 19.75 for periods 13 or more Absolute Error Absolute Period Value Forecast Error Error Squared % Error number of per 1 17 2 21 3 19 4 23 5 18 20 -2 2 4 0.111111 6 16 20.25 -4.25 4.25 18.0625 0.265625 7 20 19 1 1 1 0.05 8 18 19.25 -1.25 1.25 1.5625 0.069444 9 22 18 4 4 16 0.181818 10 20 19 1 1 1 0.05 11 15 20 -5 5 25 0.333333 12 22 18.75 3.25 3.25 10.5625 0.147727 13 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75
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19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75 19.75
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15.1132 mean absolute percentage error 5 riods in mo MAD 3 2.67 4 2.71
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INPUTS OUTPUTS Number of Periods in Moving Average = 3 Number of Periods of Data Collected = 12 MSE = 12.45 MAPE = MAD = 3.166667 LAD = OUTPUTS Forecast = 19.7 for periods 13 or more Past Period 1 2 3 4 5 6 7 8 Weighting 0.6 0.3 0.1 Absolute Error Absolute Period Value Forecast Error Error Squared % Error 1 17 2 21 3 19 4 23 19.4 3.6 3.6 12.96 0.156522 5 18 21.6 -3.6 3.6 12.96 0.2 6 16 19.6 -3.6 3.6 12.96 0.225 7 20 17.3 2.7 2.7 7.29 0.135 8 18 18.6 -0.6 0.6 0.36 0.033333 9 22 18.4 3.6 3.6 12.96 0.163636 10 20 20.6 -0.6 0.6 0.36 0.03 11 15 20.4 -5.4 5.4 29.16 0.36 12 22 17.2 4.8 4.8 23.04 0.218182 13 19.7 19.7 19.7 19.7 19.7 19.7 19.7 19.7 19.7
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  • Winter '10
  • goldstein
  • Mean absolute percentage error, seasonal factors, #VALUE, #DIV

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