Outlier Calculator
IQR fences and z-scores flag unusual points instantly.
Enter your values
ⓘ Live results
Results
- Outliers (1.5 × IQR)
- 42
- Lower fence
- 9.5
- Upper fence
- 23.5
- Q1 / median / Q3
- 14.75 / 15.5 / 18.25
- IQR
- 3.5
- Outliers by z-score > 3
- None found
- Data without outliers
- 12, 14, 15, 15, 16, 18, 19
Quick answer
A point is a mild outlier when it falls more than 1.5 × IQR below Q1 or above Q3, and an extreme outlier beyond 3 × IQR.
fences = Q1 − 1.5·IQR and Q3 + 1.5·IQR
How to use the Outlier Calculator
- 1Paste your dataset separated by commas.
- 2Check which points fall outside the fences.
- 3Decide whether each outlier is a genuine extreme value or a data-entry error before deleting anything.
Worked example
Using the values the calculator loads with:
Inputs
- Data values12, 14, 15, 15, 16, 18, 19, 42
Results
- Outliers (1.5 × IQR)42
- Lower fence9.5
- Upper fence23.5
- Q1 / median / Q314.75 / 15.5 / 18.25
- IQR3.5
- Outliers by z-score > 3None found
- Data without outliers12, 14, 15, 15, 16, 18, 19
Frequently asked questions
Should I always remove outliers?
No. Remove them only when you can show they are errors. Genuine extremes often carry the most interesting information.
IQR rule or z-scores?
IQR is safer for small or skewed samples because the mean and SD are themselves dragged around by outliers.
About this calculator
- Built and reviewed by James Whitfield · How we build and test calculators
- Report an error
Results are estimates for general information. For medical, legal, structural or financial decisions, confirm with a qualified professional.