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Outlier Detector
Find unusual values with the 1.5 and 3.0 interquartile range rules and a z score threshold.
Find outliers
Q1: — · Q3: — · IQR: —
1.5 IQR fences: —
3.0 IQR fences: —
Mean: — · SD: —
Flagged values: —
—
How to use the Outlier Detector
- Paste the data set you want to check into the box.
- Set the z score threshold you want to use for flagging values.
- Read the fences and the table of flagged values with their scores.
Features
- 1.5 and 3.0 interquartile range rules
- Adjustable z score threshold
- Position, score and fence for every flagged value
- Runs locally, no uploads
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Frequently Asked Questions
Common questions about the free online outlier detector.
Paste your numbers, then read the table of flagged values. Each row shows the position, the
value, its score and the fence it crossed.
Values below Q1 minus 1.5 times the IQR, or above Q3 plus 1.5 times the IQR, are treated as
likely outliers by this common rule.
Values outside Q1 minus 3 times the IQR or Q3 plus 3 times the IQR are far outliers and are
usually called extreme points.
A z score says how many standard deviations a value sits from the mean, so large positive or
negative scores mark unusual points.
Any value whose z score is larger in size than your threshold is flagged. The default of 2.5
catches fairly rare values.
Quartiles use linear interpolation between the ordered values, the same method as the default
percentile in most statistics software.
It shows how many interquartile ranges the value lies beyond the nearer quartile, so a larger
number means a more extreme point.
No. A flagged value is only a candidate. Check the measurement or the data entry before
deciding to remove it from the set.
Yes, but with fewer than about eight values the quartiles are less stable, so treat the flags
as hints rather than firm findings.
No. The detector runs entirely in your browser and the numbers you paste are never sent
anywhere.
Last updated: October 10, 2026