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Percentile Calculator

Find the value at any percentile of a data set, or the percentile rank of a value, with the inclusive and exclusive methods, quartiles and steps.

Results

ItemValue

Steps

StepWorking
Different textbooks and software use slightly different percentile methods, so small differences are normal. The inclusive method matches Excel’s PERCENTILE.INC and Google Sheets’ PERCENTILE.

Quick Answer

A percentile is the value below which a given share of the data falls. For the data 55, 62, 68, 70, 72, 75, 78, 81, 84, 90, the 90th percentile (inclusive method) is at position (10 − 1) × 0.9 = 8.1, so it is 84 + 0.1 × (90 − 84) = 84.6. The median (50th percentile) is 73.5.

Last updated: 3 November 2026 ·How we calculate this: the inclusive, exclusive and nearest-rank percentile methods

Table of Contents

How This Percentile Calculator Works

Paste your numbers, then choose to find the value at a percentile or the percentile rank of a value. The calculator sorts the data and uses your chosen method to find the position of the percentile, interpolating between neighboring values when needed. For a percentile rank, it counts how many values fall below and equal to your value. It also shows the quartiles and interquartile range.

Quick explanation: the 90th percentile is a value with 90% of the data at or below it.

  • 25th: the first quartile, Q1.
  • 50th: the median.
  • 75th: the third quartile, Q3.

How to Use the Percentile Calculator

  1. Paste or type your numbers.
  2. Choose value at a percentile, or percentile rank of a value.
  3. Enter the percentile or the value.
  4. Choose a method, if finding a value.
  5. Press Calculate and read the result, quartiles and steps.

Core Formulas

  • Inclusive position: h = (n − 1) × p ÷ 100, counting from 0
  • Exclusive position: h = (n + 1) × p ÷ 100, counting from 1
  • Interpolate: value = x⌊h⌋ + (h − ⌊h⌋) × (next value − x⌊h⌋)
  • Nearest rank: r = ⌈p ÷ 100 × n⌉
  • Percentile rank: (values below + ½ × values equal) ÷ n × 100

Key Terms

  • Percentile: a value below which a given percent of data falls.
  • Percentile rank: the percent of data at or below a given value.
  • Quartile: the 25th, 50th and 75th percentiles.
  • IQR: interquartile range, Q3 − Q1.
  • Interpolation: estimating a value between two known values.

Worked Example

Find the 25th percentile of 55, 62, 68, 70, 72, 75, 78, 81, 84, 90.

  • Inclusive position: (10 − 1) × 0.25 = 2.25
  • Values at positions 2 and 3 (from 0) are 68 and 70
  • P25 = 68 + 0.25 × (70 − 68) = 68.5

Real-Life Examples

  • Test scores: find the score at the 90th percentile of a class.
  • Website speed: report the 95th percentile load time, not just the average.
  • Pay bands: find the 25th, 50th and 75th percentiles of salaries.
  • Growth charts: see where a measurement ranks among others.

Percentile vs Percentage

  • Percentage: a part out of 100, like scoring 85% on a test.
  • Percentile: a ranking, like scoring better than 85% of test takers.
  • Different ideas: an 85% score could be any percentile, depending on others' scores.

Percentiles of the Example Data

PercentileValue
5th58.15
10th61.3
25th68.5
50th73.5
75th80.25
90th84.6
95th87.3
99th89.46

Which Method Should I Use?

  • Inclusive: the default in Excel PERCENTILE and Google Sheets. Good for most uses.
  • Exclusive: used by some statistics courses and Excel PERCENTILE.EXC.
  • Nearest rank: always returns an actual data value, with no interpolation.
  • Big data sets: the methods give almost the same answer.

High percentiles are popular for measuring things like response times and wait times, because averages can hide slow cases. If the 95th percentile page load is 3 seconds, then 1 in 20 visits takes 3 seconds or longer, even if the average looks fast. In the same way, salary surveys often quote the 25th, 50th and 75th percentiles to show the typical range rather than one average number. Percentiles are also robust: a single extreme value barely moves the median, while it can pull the average a long way.

Common Mistakes to Avoid

  • Forgetting to sort. Percentiles need data in order. The calculator sorts for you.
  • Mixing up percentile and percent. They measure different things.
  • Comparing methods. Use the same method when comparing results.
  • Using too little data. Percentiles of very small sets are rough.
  • Calling the max the 100th percentile in every method. Some methods do not define it.

Frequently Asked Questions

Sort the data, find the position with (n − 1) × p ÷ 100, and interpolate between neighbors.

The median.

Count values below it, add half of those equal, divide by n and multiply by 100.

Excel has PERCENTILE.INC and PERCENTILE.EXC. Choose the matching method here.

A value with 90% of the data at or below it.

Q1 is the 25th percentile, Q2 the 50th and Q3 the 75th. They are shown in the results.

Q3 − Q1, the spread of the middle half of the data.

Yes. Values on separate lines work.

Yes.

It picks the data value at rank ⌈p × n ÷ 100⌉, with no interpolation.

No. A z-score measures distance from the mean in standard deviations.

Up to 10,000.

References & Sources

SourceUsed ForLink
Wikipedia, Percentile Definitions and the different calculation methods. https://en.wikipedia.org/wiki/Percentile
NIST/SEMATECH e-Handbook, Percentiles How percentiles are estimated from data. https://www.itl.nist.gov/div898/handbook/prc/section2/prc262.htm