IQR Calculator (Interquartile Range)

Enter your dataset into the IQR Calculator and get the interquartile range along with Q1, Q2 (median), Q3, minimum, maximum, and full range. Paste up to 50 numbers separated by commas, spaces, or new lines — the calculator handles the sorting and quartile math for you.

Enter numbers separated by commas, spaces, or new lines. Up to 50 values.

Inclusive is the most common method used by Excel, R, and most statistics software.

Used to identify outliers beyond the inner and outer fences.

Results

Interquartile Range (IQR)

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Q1 — First Quartile (25th Percentile)

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Q2 — Median (50th Percentile)

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Q3 — Third Quartile (75th Percentile)

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Minimum

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Maximum

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Range (Max − Min)

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Count (n)

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Lower Outlier Fence

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Upper Outlier Fence

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Outliers Detected

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Five-Number Summary

Results Table

Frequently Asked Questions

What is the interquartile range (IQR)?

The interquartile range is the difference between the third quartile (Q3) and the first quartile (Q1): IQR = Q3 − Q1. It measures the spread of the middle 50% of a dataset, making it a robust indicator of statistical dispersion that is not affected by extreme values or outliers.

How is IQR different from the regular range?

The regular range is simply the maximum minus the minimum, which means a single extreme outlier can dramatically inflate it. The IQR only looks at the middle 50% of your data, so it gives a more reliable picture of typical spread and is much less sensitive to outliers or skewed distributions.

Can I use the IQR to find outliers?

Yes — this is one of the most common uses of the IQR. Any value below Q1 − 1.5×IQR or above Q3 + 1.5×IQR is considered a mild outlier. Values beyond Q1 − 3×IQR or Q3 + 3×IQR are classified as extreme outliers. This calculator shows both fences and flags any outliers in your dataset.

Do I need to sort my data before entering it?

No. The calculator automatically sorts your values in ascending order before computing quartiles and all other statistics. You can paste unsorted data directly from a spreadsheet or text file.

What are the different quartile methods (Inclusive vs. Exclusive vs. Tukey)?

Different software packages use slightly different interpolation rules when computing quartiles. The Inclusive (Type-7) method is the default in Excel, R, and most stats packages. The Exclusive method (Excel QUARTILE.EXC) excludes the median from both halves. Tukey's hinges split the dataset at the median and take the median of each half — it can produce slightly different Q1/Q3 values for small datasets.

Is IQR better than standard deviation?

It depends on your data. Standard deviation assumes an approximately normal distribution and is sensitive to outliers. IQR makes no distributional assumptions and is resistant to outliers, making it the preferred measure of spread for skewed data, ordinal data, or datasets with extreme values.

How are the quartiles Q1, Q2, and Q3 calculated?

After sorting the data, Q2 is the median of the full dataset. Q1 is the median of the lower half (below Q2), and Q3 is the median of the upper half (above Q2). For the inclusive method, interpolation is used when the quartile falls between two data points. The exact position depends on the method chosen.

What is the five-number summary?

The five-number summary consists of: Minimum, Q1, Median (Q2), Q3, and Maximum. Together, these five values describe the full distribution of your dataset and are used to construct box plots (box-and-whisker plots), which visually show spread and potential outliers.

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