What is difference between forecast accuracy and bias?

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Accepted Answer

Forecast accuracy measures how close the forecast is to actual results, while bias measures the tendency of the forecast to consistently over or under predict.

Forecast accuracy is the measure of how close the forecasted values are to the actual values.
Bias is the tendency of the forecast to consistently over or under predict the actual values.
Forecast accuracy is typically measured using metrics like Mean Absolute Percentage Error (MAPE) or Mean Absolute Error (MAE).
Bias can be identified by consistently seeing forecast values consistently above or below actual values.
An example of forecast accuracy would be a MAPE of 5%, indicating that the forecast is, on average, within 5% of the actual values.
An example of bias would be consistently forecasting 10% higher than the actual values.

What is difference between forecast accuracy and bias?

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