We can use the MAPE calculator below to obtain the MAPE value. Simply enter the observed values and the predicted values in the calculator below.

**Observed values:**

**Predicted values:**

**MAPE = 2.43242%**

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 O_{i} and P_{i }denote the observed and predicted values respectively. The Mean Absolute Percentage Error (MAPE) can be calculated using the formula,

MAPE = 1/n * *Σ*(|O_{i}-P_{i}|)/O_{i} x 100.