What is a interquartile range calculator?
The interquartile range measures the spread of the middle 50% of ordered data. Because it depends on quartiles instead of every distance from the mean, it is relatively resistant to extreme values.
Use this page for a transparent calculation, then compare the result with the Percentile Calculator when a different view of the same data would be useful.
How does this interquartile range calculator work?
The calculator sorts the data, obtains Q1 and Q3 with inclusive linear interpolation, subtracts Q1 from Q3, and checks values against the 1.5×IQR fences.
Before interpreting spread or position, it can help to check the center with the Median Calculator. Every tool states its assumptions so results can be reproduced.
How to use this calculator
- Enter the requested numbers in the labeled fields.
- Review unit, sample, confidence, or test choices when shown.
- Select Calculate Interquartile Range.
- Read the main result, supporting facts, and method note.
- Use Copy, Download, or Print when you need to keep the result; select Reset to start over.
If you edit any input after calculating, the old result is marked stale and hidden until you calculate again.
How should you interpret the result?
A larger IQR means the central half of the observations is more spread out. Values beyond a fence deserve review but are not automatically errors.
For another useful perspective, open the Standard Deviation Calculator; it answers a related question without changing the values you entered here.
Assumptions and limitations
Quartile conventions differ across software, especially in small samples. The IQR also ignores how values are distributed within and beyond the middle half.
Consider the Variance Calculator for a complementary summary and the Mode Calculator when your question involves another statistical property. No single statistic describes every important feature of a data set.
Frequently asked questions
Sources and methodology
The formulas and cautions on this page are documented so the calculation can be checked against authoritative statistical guidance.