Forecast a statement about the future value of a variable of interest such as demand(informed decision)types
Judgmentaluses subjective inputs, Time series uses historical data future like past, Associate models uses
explanatory variables to predict the future trend longterm movement in data seasonality short term regular
variations cyclewavelike variations of more then one year irregular variation
random varianceNaïve 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
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '09
 VinayakVenugopal
 Management, Project Management, Forecasting, Regression Analysis, absolute error Mean

Click to edit the document details