Forecast error is found by subtracting the forecast from the actual demand for a given period.

Question

BlackTom AI · Accepted Answer

The statement to evaluate is: 'Forecast error is found by subtracting the forecast from the actual demand for a given period.'
Option 1: True. If you interpret 'subtracting the forecast from the actual' literally as Actual minus Forecast, then this yields a number that represents how far off the forecast was, with sign indicating whether actual exceeded the forecast (positive) or fell short (negative). However, many forecasting texts and calculators define forecast error as Forecast minus Actual, not Actual minus Forecast, so this option can be considered incorrect depending on the convention being used.
Option 2: False. The conventional definition of forecast error is typically Forecast minus Actual (Error = Forecast − Actual). This means the error is found by subtracting the actual demand from the forecast, not the other way around. Using Forecast − Actual aligns with common error metrics like Mean Signed Error and is the basis for several performance measures where the sign conveys bias (whether forecasts tend to overpredict or underpredict).
Additional nuance: In some contexts, people use Actual − Forecast and then report the magnitude as the absolute error, MAD, or RMSE without regard to sign. When a problem explicitly states a different convention, the interpretation may differ. In this item, the given answer indicates that the statement is not aligned with the standard convention (Forecast − Actual), hence the classification as False.
In summary, the core distinction is the order of subtraction defining the error value and its sign. The conventional approach uses Forecast minus Actual, which makes the statement as written (Actual minus Forecast) not consistent with that common convention.

Forecast error is found by subtracting the forecast from the actual demand for a given period. 判断题

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