To calculate the Mean Absolute Deviation (MAD), we need to find the absolute deviations between the actual values and forecasted values for each year, then calculate their average.

1. Calculate Absolute Deviations for Each Year:

   • Year 1: |214 - 210| = 4
   • Year 2: |216 - 200| = 16
   • Year 3: |226 - 230| = 4

2. Calculate the MAD:

   • Sum of Absolute Deviations = 4 + 16 + 4 = 24
   • MAD = Total Absolute Deviation / Number of Observations = $\frac{24}{3} = 8$

So, the resulting MAD value is 8.

Answer: 8

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Would you like a breakdown of MAD in different forecasting scenarios or have any questions?

1. How would MAD differ with a larger dataset?
2. What are alternative measures to MAD for assessing forecast accuracy?
3. How can outliers affect MAD and similar accuracy metrics?
4. What is the significance of the MAD value in decision-making?
5. How can MAD be useful in inventory management?

Tip: MAD is often used to evaluate forecast accuracy because it is simple and intuitive, highlighting typical forecast errors without regard to direction (positive or negative).