| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960 | [discrete][[esql-agg-median-absolute-deviation]]=== `MEDIAN_ABSOLUTE_DEVIATION`*Syntax*[source,esql]----MEDIAN_ABSOLUTE_DEVIATION(expression)----*Parameters*`expression`::Expression from which to return the median absolute deviation.*Description*Returns the median absolute deviation, a measure of variability. It is a robuststatistic, meaning that it is useful for describing data that may have outliers,or may not be normally distributed. For such data it can be more descriptivethan standard deviation.It is calculated as the median of each data point's deviation from the median ofthe entire sample. That is, for a random variable `X`, the median absolutedeviation is `median(|median(X) - X|)`.NOTE: Like <<esql-agg-percentile>>, `MEDIAN_ABSOLUTE_DEVIATION` is      <<esql-agg-percentile-approximate,usually approximate>>.[WARNING]====`MEDIAN_ABSOLUTE_DEVIATION` is also {wikipedia}/Nondeterministic_algorithm[non-deterministic].This means you can get slightly different results using the same data.====*Example*[source.merge.styled,esql]----include::{esql-specs}/stats_percentile.csv-spec[tag=median-absolute-deviation]----[%header.monospaced.styled,format=dsv,separator=|]|===include::{esql-specs}/stats_percentile.csv-spec[tag=median-absolute-deviation-result]|===The expression can use inline functions. For example, to calculate the themedian absolute deviation of the maximum values of a multivalued column, firstuse `MV_MAX` to get the maximum value per row, and use the result with the`MEDIAN_ABSOLUTE_DEVIATION` function:[source.merge.styled,esql]----include::{esql-specs}/stats_percentile.csv-spec[tag=docsStatsMADNestedExpression]----[%header.monospaced.styled,format=dsv,separator=|]|===include::{esql-specs}/stats_percentile.csv-spec[tag=docsStatsMADNestedExpression-result]|===
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