BU385 Chapter Notes - Chapter 3: Simple Linear Regression, Squared Deviations From The Mean, Mean Squared Error
Document Summary
Demand forecast the esimate of expected demand during a speciied future period. Features common to all forecasts: forecasing techniques generally assume that the same underlying causal system that existed in the past will coninue to exist in the future, forecasts are rarely perfect; actually results usually difer from predicted values. No one can predict precisely how related factors will impinge upon the variable in quesion. Allowances should be made for inaccuracies: forecasts for groups of items tend to be more accurate than forecasts for individual items. Ex. forecast for total sales of a new t shirt will be more accurate than the forecast for each size/colour: forecast accuracy decreases the farther the forecasted ime period is into the future. Forecasing horizon the range of ime periods we are forecasing for. Steps in the forecasing process: determine the purpose of the forecast. There are two general approaches to forecasing: judgemental and quanitaive.
