Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model.

Mean Squared Error

A measure of the average squared difference between the estimated values and what is estimated, often used in statistics and machine learning to assess the accuracy of models.

Coefficient of Correlation

A statistical measure that indicates the extent to which two variables fluctuate together. A higher coefficient suggests a stronger relationship.

Overall Error

Overall Error encompasses the total inaccuracies or deviations from a standard or expected outcome, combining both systematic and random errors.