Outlier Calculator
Calculate outlier using your data.
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What this tool does
Calculate outlier using your data. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
How to use the Outlier Calculator
- Enter or select numbers (comma or whitespace separated).
- Read the calculated result; change any measurement to compare alternatives.
Formula
Tukey fences: lower = Q1 − 1.5×IQR, upper = Q3 + 1.5×IQR; values outside the fences are flagged as outliers
- data
- Numbers (comma or whitespace separated)
Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
Worked example
For outlier calculator, the following measurements illustrate the exact method: Numbers (comma or whitespace separated): 10,12,11,13,12,11,10,45,12,13.
Inputs
- Numbers (comma or whitespace separated)10,12,11,13,12,11,10,45,12,13
Result
- Outliers found1
- Outlier values45
- Lower fence8.38
- Upper fence15.38
- Q111
- Q312.75
- IQR1.75
Results explained
- Outliers found
- Outliers found from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- Outlier values
- Outlier values from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- Lower fence
- Lower fence from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- Upper fence
- Upper fence from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- Q1
- Q1 from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- Q3
- Q3 from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
- IQR
- IQR from the formula above. Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
Frequently asked questions
Tukey fences: lower = Q1 − 1.5×IQR, upper = Q3 + 1.5×IQR; values outside the fences are flagged as outliers
Tukey's 1.5×IQR rule flags candidates for investigation, not automatic deletion — an outlier can be a data error, a rare real event, or the most interesting observation in the set.
Enter numbers only, in the units and format each label describes. Remove missing values rather than substituting zero, unless zero is a real observation.
No. Results describe the numbers you entered. Statistical inference also depends on sampling design, independence, model fit and interpretation; a p-value is not the probability that a hypothesis is true.
No. Every calculation, including the distribution algorithms, runs entirely in your browser.