Value at a Given Percentile Calculator

Enter a data set and a percentile to find the value at it.

How it is calculated

The values are sorted from smallest to largest, with n the number of values. The tool then computes a zero-based rank r = p ÷ 100 × (n − 1), so the smallest value sits at rank 0 and the largest at rank n − 1. If r falls between two positions, the answer is interpolated: value = x⌊r⌋ + (r − ⌊r⌋) × (x⌊r⌋+1 − x⌊r⌋). At p = 0 you get the minimum and at p = 100 the maximum. This is the inclusive method that spreadsheet PERCENTILE.INC uses; other methods give slightly different numbers for small data sets. Separate values with spaces or commas, with a dot as the decimal mark (a comma always splits numbers). The percentile must be from 0 to 100, and any non-numeric item stops the calculation.

Worked example

Find the 90th percentile of 12, 15, 11, 20, 18, 25, 14, 30. Sorted: 11, 12, 14, 15, 18, 20, 25, 30, so n = 8. Rank: 0.90 × (8 − 1) = 6.30, shown as the rank position. Rank 6 is the value 25 and rank 7 is 30. Interpolate 0.30 of the way: 25 + 0.30 × (30 − 25) = 25 + 1.5 = 26.50.

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Common mistakes

  • Typing a decimal comma such as 2,5 in the list: a comma separates values, so it is read as the two numbers 2 and 5; use 2.5.
  • Entering the percentile as a fraction (0.9) instead of a number from 0 to 100: 0.9 gives the 0.9th percentile, close to the minimum.
  • Expecting the result to be one of your data values: it is interpolated, so 26.50 is not in the list, which is normal.
  • Comparing the result with another tool without checking its method: some use rank p × (n + 1) and give a different answer on small samples.
  • Reading the rank position as a 1-based position: it starts at 0 for the smallest value.

About this calculator

Finding the value at a given percentile means locating the point in a sorted data set below which that percentage of observations falls. When the desired percentile lands exactly on a data point, that is the answer; when it lands between two ranks — which is the usual case — this calculator uses linear interpolation between the two neighboring values, the same approach used by common tools like Excel's PERCENTILE function and most statistical software's default percentile method.

Percentiles built this way show up constantly outside pure statistics: standardized test scores are reported as percentiles so parents can see how a child compares to peers, pediatric growth charts plot height and weight percentiles by age, and software engineers track “p95” or “p99” latency — the response time below which 95% or 99% of requests fall — as a key performance benchmark.

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