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Percentile Range Calculator | Get Spread Between Two Percentiles

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Compute the spread between any two percentiles — the interquartile range, P10–P90, or any custom band — with the interpolation shown. Understand the middle of your data and identify outliers with the 1.5×IQR rule.

Last updated: June 2026 · Free · No sign-up required

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Results

Enter values above and click Calculate to see your result instantly.

Quick reference

DataBandValuesRange
1–10P25–P753.25 / 7.754.5
1–10P10–P901.9 / 9.17.2
15, 20, 35, 40, 50P10–P9017 / 4629
Any dataP0–P100min / maxfull range

info Percentile Range Calculator

Free math calculator — enter your numbers and get an instant, accurate result.

info Private by design

Everything runs locally in your browser. No uploads, no accounts, no tracking.

info Works everywhere

Fully responsive and mobile-friendly — calculate on any device, any time.

info Educational

Includes the formula and step-by-step explanation so you understand the math, not just the answer.

Interpretation guide

BandWhat it captures
P25–P75 (IQR)Middle 50% — standard outlier-resistant spread
P10–P90Middle 80% — common in salary and growth charts
P5–P95Middle 90% — reference intervals in medicine
P2.5–P97.595% reference range, mirrors a 95% CI

lightbulb Worked example

Let's say you are using the Percentile Range Calculator. Computes the spread between any two percentiles of a data set — interquartile range, P10–P90 or any custom band. Enter the values that match your situation into the input fields and press calculate — using realistic numbers makes the result directly useful for you.

Result: The calculator instantly applies the formula Range = P(upper) − P(lower), percentiles by linear interpolation: h = (n−1)p/100, v = x⌊h⌋ + (h−⌊h⌋)(x⌊h⌋₊₁ − x⌊h⌋) and returns the result with appropriate precision.

What this means: Read the result in the context of what you are measuring. The step-by-step breakdown lets you confirm the math and understand which input most affects the outcome.

Formula & methodology

Formula: Range = P(upper) − P(lower), percentiles by linear interpolation: h = (n−1)p/100, v = x⌊h⌋ + (h−⌊h⌋)(x⌊h⌋₊₁ − x⌊h⌋)

The Percentile Range Calculator is built on a well-established calculation method. It uses the formula Range = P(upper) − P(lower), percentiles by linear interpolation: h = (n−1)p/100, v = x⌊h⌋ + (h−⌊h⌋)(x⌊h⌋₊₁ − x⌊h⌋) to turn your inputs into a reliable result. Computes the spread between any two percentiles of a data set — interquartile range, P10–P90 or any custom band. The steps are shown on the page so you can follow the reasoning from input to output.

  1. Paste your data set — at least two numbers, any separator.
  2. Pick the lower and upper percentiles (defaults 25 and 75 give the interquartile range).
  3. Values are sorted and each percentile is found by linear interpolation between the two nearest order statistics (the R-7 method, identical to Excel's PERCENTILE.INC).
  4. The range is simply the upper percentile minus the lower.

Worked example: data 1–10 with P25 and P75 → P25 = 3.25, P75 = 7.75, interquartile range = 4.5.

Authoritative source: Wolfram MathWorld

Frequently asked questions

What is a percentile range?
The Percentile Range Calculator is free, private, and accurate: it runs entirely in your browser (no uploads, no accounts), applies the standard calculation, and explains each step so you can verify the result. Computes the spread between any two percentiles of a data set — interquartile range, P10–P90 or any custom band. There is no limit on usage, and it works on any device.
How are the percentile values calculated?
Percentiles use linear interpolation: for the p-th percentile, compute the position h = (n − 1)p ÷ 100, then interpolate between the surrounding sorted values: v = x⌊h⌋ + (h − ⌊h⌋)(x⌊h⌋₊₁ − x⌊h⌋). This gives a continuous percentile definition that works for any data set size. The calculator shows the interpolation for your chosen percentiles.
Why use the IQR instead of the full range?
The full range only depends on the minimum and maximum, so a single outlier makes it misleading. The interquartile range (IQR), defined as P75 − P25, describes the spread of the middle half of the data and is robust to extreme values. Use the IQR for skewed data or when outliers are present, and reserve the full range for symmetric data without extremes.
What is the P10–P90 range used for?
The Percentile Range Calculator is a free online tool that computes the spread between any two percentiles of a data set — interquartile range, p10–p90 or any custom band. You enter a few values, and it returns an accurate result together with a step-by-step explanation, so it works as both a calculator and a quick reference for the underlying concept.
Can I compute a single percentile with this tool?
Yes — in addition to range modes like the IQR (P75 − P25) and P10–P90, the calculator accepts a single percentile value and returns it directly. Enter the percentile you need and the sorted data position and interpolated value are shown. This covers the common case of reporting a specific percentile like the median (P50) or the 95th.
Which percentile bands are the most useful to compare?
The interquartile range (P25–P75) describes the middle half of your data, while P10–P90 covers the central 80% and is less sensitive to a few extreme values. Analysts often pair the range with the 1.5×IQR rule to flag outliers — anything below P25 − 1.5×IQR or above P75 + 1.5×IQR deserves a closer look.
How is each percentile actually estimated from the data?
Each percentile is estimated by linear interpolation: rank h = (n−1)p/100, then value = x〉h⌫ + (h−〉h⌫)(x〉h⌫₊₁ − x〉h⌫). In plain terms, the percentile usually falls between two data points, and the result blends them proportionally instead of snapping to the nearest one.
What does it mean when the range between two percentiles is zero?
It means many values in your data are tied — for example, half a class scoring exactly 70% makes P25 through P75 all equal 70. A zero range is informative, not an error: it tells you the data is heavily clumped at one value.
Why might my result differ slightly from my stats software?
There are at least nine standard interpolation methods, and small data sets can give slightly different percentiles depending on which one is used. This tool uses linear interpolation on h = (n−1)p/100; spreadsheet or stats-package defaults may differ, so a gap of a fraction of a unit between tools is normal.

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