The mean absolute deviation or MAD as it is often abbreviated, of a dataset is the average or "mean" distance between each data point from the data set and the mean/average. This will give you an idea of the amount of variability in a dataset. MAD can be calculated from both observations and the arithmetic average (mean) of those observations. Another option when calculating MAD is to calculate based on actual data minus forecasted data. If forecasting or being used for future analysis you can apply different weights to your forecast or use exponential smoothing in an attempt to make your forecast more accurate. In most cases however mean absolute deviation uses actual data.
How to Calculate Mean Absolute Deviation
Example of Mean Absolute Deviation
The marketing team has been posting pictures and videos online as part of a campaign. The last 6 campaign posts received the following number of likes: 15,11,13,16,18 and 17.
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