{"id":236612,"date":"2024-06-21T00:07:41","date_gmt":"2024-06-21T00:07:41","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/?p=236612"},"modified":"2024-06-21T00:07:41","modified_gmt":"2024-06-21T00:07:41","slug":"how-to-calculate-mape-value","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/how-to-calculate-mape-value\/","title":{"rendered":"How to calculate MAPE value?"},"content":{"rendered":"

The Mean Absolute Percentage Error (MAPE) value is calculated by taking the absolute percentage error between actual and predicted values for a time series data set, then averaging these errors across all data points and expressing it as a percentage.<\/b><\/p>\n

MAPE is a common metric used to evaluate the accuracy of forecasting models, particularly in fields like finance, sales, and supply chain management. Calculating the MAPE value allows businesses to understand how well their forecasting model is performing in predicting future values based on historical data.<\/p>\n

To calculate MAPE value, follow these steps:
\n1. Subtract the predicted value from the actual value for each data point.
\n2. Divide the absolute value of the difference by the actual value.
\n3. Sum all the percentage errors.
\n4. Divide the total by the number of data points.
\n5. Multiply the result by 100 to get the MAPE value as a percentage.<\/p>\n

To illustrate this with an example, let’s say you have a time series data set where the actual values are [100, 200, 300] and the predicted values are [110, 190, 310]. Follow the steps above to calculate the MAPE value.<\/p>\n

Calculating MAPE for the first data point:
\n1. |100 – 110| \/ 100 = 0.1
\n2. Absolute Percentage Error = 10%
\nContinue this process for all data points, then average the absolute percentage errors and multiply by 100 to get the MAPE value.<\/p>\n

In this example, the MAPE value would be calculated as follows:
\n(10% + 5% + 3.33%) \/ 3 = 6.11%<\/p>\n

Therefore, the MAPE value for this time series data set is 6.11%.<\/p>\n

Now that we understand how to calculate MAPE value, let’s address some common questions related to this topic.<\/p>\n

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