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Mean Absolute Deviation Calculator

Enter numeric data to measure dispersion using mean absolute deviation (MAD).

Mean

19.5000

Mean absolute deviation

4.5000

How to Use This Calculator

  1. Paste your dataset into the input box.
  2. Review the computed mean and mean absolute deviation.
  3. Use MAD to gauge average deviation from the mean.
  4. Compare MAD values across datasets to assess consistency.

Formula

MAD = Σ|xi − μ| / n

μ = Σxi / n

MAD is a robust measure of dispersion less sensitive to outliers than standard deviation.

Full Description

MAD is the average distance between each observation and the mean. It complements range and standard deviation, especially in data sets where robustness against extreme values is crucial.

Lower MAD indicates tighter clustering around the mean, while higher MAD suggests greater variability.

Frequently Asked Questions

Is MAD the same as mean absolute error?

They share the same formula; MAD applies to raw data, while mean absolute error compares predictions to actuals.

Can I use MAD to detect outliers?

Use MAD alongside IQR or standard deviation to flag unusual points, as MAD itself reflects average deviation.

How many points do I need?

At least one value is required, though more data provide a stable estimate.

Does MAD rely on the mean?

Yes. It measures absolute deviations from the mean. For median-based robustness, use the median absolute deviation (MADmedian).