Median Absolute Deviation Measure
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A Median Absolute Deviation Measure is a statistical dispersion measure of univariate quantitative data based on absolute deviation to a median value.
- Example(s):
- for the data set {2, 2, 3, 4, 14}: [math]\displaystyle{ \frac{|2 - 3| + |2 - 3| + |3 - 3| + |4 - 3| + |14 - 3|}{5} = 2.8 }[/math].
- …
- Counter-Example(s):
- See: Absolute Deviation, Median Statistic, Mean Squared Error, Population Statistic, Robust Statistics, Statistical Dispersion.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Median_absolute_deviation Retrieved:2020-7-24.
- In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample.
For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median [math]\displaystyle{ \tilde{X}=\operatorname{median}(X) }[/math] : : [math]\displaystyle{ \operatorname{MAD} = \operatorname{median}( |X_i - \tilde{X}|) }[/math] that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values.
- In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample.