forecasting_exercise

May 19th, 2015
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Brookhaven College
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error forecasting us the weighted moving average method The forecasting technique followed in the problem appears to be that forecast for period t= Actual demand for period (t-1)

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Forecasting ExerciseName:Affiliation No:Institution Name:Task:Submission Date: Forecasting ExerciseabcfPeriodQuarterForecastActual DemandD10Forecast with 3 MAErrorForecast with ES(ErrorForecast with 3WMA(0.50,0,0.15).35 G10Error14Q 2008200220221.67-1.6721Q 2009220215220.67-5.6732Q 2009215210217.27-7.2743Q 20102102202155212.917.09213.256.7554Q 200922022521510217.167.84215.759.2561Q 2010225240218.3321.67221.8718.132211972Q 2010240255228.3326.67232.7522.25231.7523.2583Q 2010260240.0020246.1013.90245.2514.7594Q 2010270251.6718.33254.4415.56255.2514.75101Q 2011261.67263.78MAD=16.947.8014.63MSE=408.33182.37293.56MAPE=6.785.055.89From Excel, the formulas used: For (a) For (bFor (c)For (f)d). Forecasting error using the exponential smoothing techniqueAll the three error criteria have the lowest values for ES (. So, exponential smoothing with appears to be the best forecasting method.e). error forecasting us the weighted moving average methodThe forecasting technique followed in the problem appears to be that forecast for period t= Actual demand for period (t-1)ReferencesChamplain College Transportation and Logistics RAC: BJ72: Demand Forecastinghttps://heizerrenderom.wordpress.com/2013/05/16/guest-post-beat-the-instructor-a-classroom-forecasting-exer

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