Outlier calculator
Uses Tukey's fences: any value beyond them is flagged as an outlier worth checking before analysis.
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How to use it
- Enter data (separate numbers with commas, spaces or new lines) and multiplier k.
- The result appears straight away and updates as you edit.
- Copy the result, or copy a link that keeps the same values to share it.
How it is calculated
Lower fence = Q1 - k × IQR, upper fence = Q3 + k × IQR, with k = 1.5 for outliers and 3 for extreme outliers; quartiles use the median-of-halves method.
Example
Inputs: Multiplier k = 1.5 (outliers). Result: Outliers: 50; Number of outliers: 1; Lower fence: -4.5.
Limits and caveats
- An outlier is not necessarily an error; check where it came from before removing it.
- Other software may compute quartiles differently, which shifts the fences slightly.
Questions about this tool
Why 1.5 × IQR?
It is John Tukey's box plot rule. On normally distributed data it flags only about 0.7% of values.
Should I delete outliers?
Only when they are proven entry or measurement errors. If they are real, report them or use robust measures such as the median.
How many values do I need?
At least four, though the rule is more dependable with twenty or more.