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Mean Absolute Deviation Calculator

The average distance from the mean, without squaring — a spread measure in the same units as the data and easier to explain than a standard deviation.

MAD = Σ|xᵢ − x̄| ÷ n.

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Mean absolute deviation
2.4
Mean
Mean deviation from the median
Sample standard deviation
Population standard deviation
MAD ÷ σ (0.798 if normal)
Count
Reviewed September 2026. Pure mathematics: the result does not depend on where you are. Terminology follows the Australian Curriculum (maths, brackets, decimal point).
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About mean absolute deviation

How the mean absolute deviation calculator works

MAD = Σ|xᵢ − x̄| ÷ n. Squaring is what makes the standard deviation mathematically convenient, but it also makes it larger than the typical distance and harder to interpret. The mean absolute deviation is literally the average gap.

For normally distributed data MAD ≈ 0.7979 σ, so the standard deviation is about 25% larger than the average deviation it is often taken to be.

Formula: MAD = Σ|xᵢ − x̄| / n

Worked examples

InputsMean absolute deviationNote
2, 4, 6, 8, 102.4MAD = 2.4
Identical values0MAD = 0
With one far point36.75MAD is far below the SD

Frequently asked questions

What is the mean absolute deviation?

The average distance of the values from their mean, using absolute values instead of squares.

How is it different from the standard deviation?

The SD squares the deviations first, which weights far points more heavily and makes the result larger. For normal data the SD is about 25% bigger.

Which should I use?

The MAD if you want an honest "typical distance" that a non-specialist will understand; the SD if you need the mathematics that follows from it — confidence intervals, regression, most of statistics.

Why does statistics prefer squaring?

Because squared deviations have clean algebra: they decompose, add across independent sources, and lead to closed-form estimators. Absolute values do none of that.

Is deviation from the median different?

Yes, and it is always smaller or equal — the median is the point that minimises total absolute distance, just as the mean minimises squared distance.

Where these figures come from

Last checked: September 2026. Formulas are fixed by mathematics and do not change with tax years or regulations.