A positive forecast error indicates that the forecasting method has done what to the dependent variable?

A positive forecast error reflects a situation where the forecasted value is less than the actual observed value of the dependent variable. In other words, the forecasting method predicted a value that was lower than what actually occurred. This means that the forecast underestimated the true outcome.

For example, if a company forecasted sales to be 100 units, but the actual sales turned out to be 120 units, the forecast error would be calculated as the actual value minus the forecasted value (120 - 100), resulting in a positive error of 20. This illustrates that the forecasting method did not adequately capture the anticipated increase in sales.

This understanding is essential when evaluating the effectiveness of a forecasting method, as it provides insights on whether adjustments are necessary for future forecasts. By recognizing that a positive error indicates an underestimation, businesses can refine their forecasting techniques and improve accuracy over time.