Median absolute deviation in the context of Robust measures of scale

Median absolute deviation in the context of Robust measures of scale

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👉 Median absolute deviation in the context of Robust measures of scale

In statistics, robust measures of scale are methods which quantify the statistical dispersion in a sample of numerical data while resisting outliers. These are contrasted with conventional or non-robust measures of scale, such as sample standard deviation, which are greatly influenced by outliers.

The most common such robust statistics are the interquartile range (IQR) and the median absolute deviation (MAD). Alternatives robust estimators have also been developed, such as those based on pairwise differences and biweight midvariance.

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👉 Median absolute deviation in the context of Robust measures of scale
Median absolute deviation in the context of Average absolute deviation

Median absolute deviation in the context of Average absolute deviation

The average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any reference value related to the given data set. AAD includes the mean absolute deviation and the median absolute deviation (both abbreviated as MAD).

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