Forecast- a statement about the future value of a variable of interest such as demand(informed decision)-types Judgmental-uses subjective inputs, Time series- uses historical data future like past, Associate models uses explanatory variables to predict the future trend- long-term movement in data seasonality short term regular variations cycle-wavelike variations of more then one year irregular variation- random variance-Naïve forecast- any period equals the previous periods actual value exponential smoothing- most recent observations highest perceived value weighted average prev. forecast+% of forecast error seasonal variations- regular repeating movement in series values that can be tied to reoccurring events seasonal relative % of ave. or trend Central moving ave.- ave. positioned at the center of the data that were used to compute it. Predictor values- predict values of variable interest regression- techniques for fitting a line to a set of points least squares line- min. sum of squares deviation around the line Mean absolute deviation(MAD)-ave. absolute error Mean squared
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