Accurately measure the average difference between your actual observations and their corresponding predictions with our Mean Prediction Error Calculator. This essential statistical tool helps evaluate the bias of your predictive models, providing insights into systematic over or underestimation. Easily analyze forecast accuracy for various applications, from finance to scientific research.
Formula:
The Mean Prediction Error (MPE) is calculated using the following formula:
MPE = (1/n) * ∑(Actuali - Predictedi)
- MPE: Mean Prediction Error
- n: The total number of observations (or predictions)
- Actuali: The i-th actual observed value
- Predictedi: The i-th predicted value
- ∑: Summation over all observations