Boneyard Tools

Outlier Calculator

Paste a data set to detect outliers with Tukey's rule. The calculator computes Q1, Q3 and the interquartile range, sets fences at 1.5 times the IQR, and flags every value beyond them.

How to find outliers

  1. Enter your numbers separated by commas, spaces or new lines.
  2. The calculator finds Q1, Q3 and the fences at 1.5 times the IQR.
  3. Review the flagged outliers and copy the cleaned data set.

Examples

One clear outlier

10, 12, 14, 15, 16, 18, 20, 100
Fences 6 to 26, outlier = 100

No outliers

10, 12, 14, 15, 16, 18, 20, 22
No values fall outside the fences

Frequently asked questions

How does this calculator detect outliers?

It uses Tukey's fences. It finds the first and third quartiles, computes the interquartile range (IQR = Q3 minus Q1), then sets a lower fence at Q1 minus 1.5 times the IQR and an upper fence at Q3 plus 1.5 times the IQR. Any value beyond a fence is an outlier.

What is the difference between this and an IQR calculator?

An IQR calculator focuses on the spread of the middle half of the data. This tool uses the same quartiles but its job is to identify which specific values are outliers and to return a cleaned data set with them removed.

Which quartile method is used?

Linear interpolation between closest ranks, matching Excel PERCENTILE.INC and NumPy. It is the same method as this site's interquartile range calculator, so the two tools always agree on Q1 and Q3.

Should I always remove the outliers it finds?

Not automatically. Tukey's rule flags values that are unusual relative to the rest, but an outlier can be a genuine data point worth investigating rather than an error. Use the flag as a prompt to review, not as an instruction to delete.

What does the 1.5 multiplier mean?

The 1.5 times IQR fences are the standard definition of a mild outlier and are what box plots use for their whiskers. A wider multiplier of 3 times the IQR marks extreme outliers; this calculator uses the common 1.5 threshold.

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