What is the mean absolute deviation (MAD) when given forecast errors of -1, 4, 8, and -3?

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To find the mean absolute deviation (MAD), you need to calculate the absolute errors from the forecasted values, then find the average of those absolute errors.

The first step involves converting each forecast error into its absolute value:

The absolute value of -1 is 1.
The absolute value of 4 is 4.
The absolute value of 8 is 8.
The absolute value of -3 is 3.

Next, you sum these absolute values: 1 + 4 + 8 + 3 = 16.

Now, you need to divide this total by the number of errors to find the average. In this case, there are 4 errors:

MAD = Total Absolute Errors / Number of Errors = 16 / 4 = 4.

Thus, the mean absolute deviation of the forecast errors is 4. This value accurately reflects the average magnitude of the forecast errors and indicates how far off the forecasts are, irrespective of the direction of the error (over or under the actual value). This calculation is essential in supply chain and operations management as it helps assess the accuracy of forecasts, allowing for better inventory management and decision-making processes.