The relative mean absolute difference is equal to twice the Gini coefficient which is defined in terms of the Lorenz curve.
This relationship gives complementary perspectives to both the relative mean absolute difference and the Gini coefficient, including alternative ways of calculating their values.
The mean absolute difference is invariant to translations and negation, and varies proportionally to positive scaling.
If, additionally, the random variable can only take on values that are greater than or equal to zero, then its relative mean absolute difference will be less than 2.
Both the standard deviation and the mean absolute difference measure dispersion—how spread out are the values of a population or the probabilities of a distribution.