Statistics & Probability

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Median Absolute Deviation Calculator.

Calculate the median absolute deviation around the sample median.

On-device calculationNo signup
01

Set your values

Results update as you type.

median: 3

median

3.000000
medianAbsoluteDeviation: 1

medianAbsoluteDeviation

1.000000

Results update automatically as you type.

Use Cases

Assess data variability in research

Use MAD to understand the spread of your data when outliers are present, giving a more robust measure than standard deviation.

Example: Comparing test scores from different classes where some scores are extreme.

Quality control in manufacturing

Monitor process consistency by tracking the median absolute deviation of product measurements to detect shifts in variability.

Example: Checking the consistency of bottle fill volumes in a production line.

Frequently Asked Questions

What is median absolute deviation (MAD)?
Median absolute deviation (MAD) is a measure of statistical dispersion. It is the median of the absolute deviations from the data's median. It is more robust to outliers than standard deviation.
How do I use this calculator?
Enter your data values separated by commas or spaces. The calculator will compute the median of your data, then find the absolute deviation of each value from that median, and finally take the median of those deviations to give you the MAD.
Why use MAD instead of standard deviation?
MAD is less sensitive to outliers than standard deviation. If your data contains extreme values, MAD provides a more reliable measure of variability, making it useful in robust statistics.

Tips & Common Mistakes

Tips

  • Ensure your data values are numeric and separated by commas or spaces for accurate calculation.
  • MAD is robust to outliers, making it a good choice when your data contains extreme values.
  • For a normal distribution, MAD is approximately 0.6745 times the standard deviation.
  • Use MAD to compare variability across datasets that have different scales.

Common Mistakes to Avoid

  • Entering non-numeric characters or leaving empty fields, which can cause errors.
  • Confusing MAD with mean absolute deviation (which uses the mean instead of the median).
  • Using MAD without considering the sample size, as it may be less stable for very small datasets.

Last updated: August 13, 2026