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test study stuff - Forecasting Lesson 1 Exponential...

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Forecasting Lesson 1 Exponential Smoothing is F t+1 = alphaAt + (1-alpha)Ft. so that’s alpha times previous demand +1-alpha*previous forecast. Double exponential - St = alpha*actual sales + 1-alpha * forecast on that line. Forecast parameter influences responsiveness (Large alpha, small n) and stability (small alpha, largen n) smooth random shocks. MSE prefers small frequent errors. MAPE is more reliable than Mean forecast error Individual forecasts are almost always wrong but the average forecast error should be close to zero. Further intp the future, the less accurate the forecast is likely to be It is easier to forecast demand for groups of items than for individual items. It is easier to forecast demand for a month than demand for a day. If you know demand will drop you want an initial reduction of periods in moving average to make it more responsive and wait for the long term to increase the periods. Lesson 2 Double exponential incorporated trends Forecasting with seasonality – account for trend using regression.
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