The MAPE (Mean Absolute Percentage Error) calculator allows us to calculate how accurately our regression model predicts the data values. If the MAPE value is high then it means that the regression model has a higher degree of error. In this case, the difference between the actual observed values and the predicted values is large which means that the regression model is not a good fit for the data.
On the other hand if the MAPE value is low, it means that the observed and predicted values lie close to each other and hence the regression model is a good fit for the given data.
Suppose that we are given ‘n’ data values. Let Oi and Pi denote the observed and predicted values respectively. The Mean Absolute Percentage Error (MAPE) can be calculated using the formula,\text{MAPE}= \frac{1}{n}\sum \frac{|O_i-P_i|}{O_i}\times 100
Since the above formula involves a lot of calculations, we can simply use the calculator below to obtain the MAPE value. Simply entering the observed values and the predicted values below gives us the required result.
Observed values:
Predicted values:
MAPE = 2.43242%
