The **mean absolute percentage error (MAPE)** is a metric that tells us how far apart our predicted values are from our observed values in a regression analysis, on average. It is calculated as:

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

where:

- Σ is a fancy symbol that means “sum”
- P
_{i}is the predicted value for the i^{th}observation - O
_{i}is the observed value for the i^{th}observation - n is the sample size

To find the MAPE for a regression, simply enter a list of observed values and predicted values in the two boxes below, then click the “Calculate” button:

**Observed values:**

**Predicted values:**

**MAPE = 2.43242%**