Percentile Calculator
Where does one value sit in the distribution?
Percentile Calculator
Find the value at any percentile, or the percentile rank of a specific value.
e.g. 90 for P90
Values are sorted and interpolated linearly between the two nearest observations, the same convention as Excel's PERCENTILE.INC.
Result
73.7
is the P90 value
- Percentile rank of 62
- 68.8%
- Median (P50)
- 45
- Count
- 8
- Mean
- 46.625
A percentile rank is the share of observations at or below the value, with ties split evenly.
Embed this calculator
Put this calculator on your own site with the snippet below. The frame contains the tool only, reports its own height, and carries a visible link back to the full page. Embedding is free; keep the attribution link as it is, and do not wrap the frame in a way that hides it.
Preparing the embed code for this page...
What This Calculator Does
The Percentile Calculator answers two related questions: which value sits at a given percentile, and what percentile a particular value occupies. It sorts the data, interpolates between observations, and splits ties evenly.
How It Works
Percentiles divide a sorted data set into 100 equal parts. This tool uses linear interpolation between the two nearest observations — the same convention as Excel’s PERCENTILE.INC and NumPy’s default “linear” method. Percentile rank works the other way: count the values below the target, add half of any exact ties, and divide by the number of observations.
Example
For 15, 20, 35, 40, 50, 62, 71, and 80, the 90th percentile has rank (8 − 1) × 0.9 = 6.3, which interpolates to 71 + 0.3 × (80 − 71) = 73.7. The value 62 has five values below it and one tie, so its percentile rank is (5 + 0.5) / 8 = 68.75%.
Formula
rank = (n − 1) × p / 100; value = x⌊rank⌋ + (rank − ⌊rank⌋)(x⌈rank⌉ − x⌊rank⌋)rank% = (values below + ties / 2) / n × 100Reading the Results
Percentile value
The data value at the requested percentile. At P90, roughly 90% of observations fall at or below it.
Percentile rank
The share of observations at or below the value you entered. Ties are split evenly so the rank does not jump when duplicates exist.
Sources and References
NIST/SEMATECH e-Handbook of Statistical Methods
Percentile and quantile definitions
NIST notes that several percentile conventions exist and that the chosen definition should be stated with the result.
References identify the method or data behind this calculator. Where a standard or tariff changes, the current edition applies, and the assumptions stated above take precedence over a remembered figure.
Frequently Asked Questions
What is the difference between a percentile and a percentage?
A percentage is a fraction of a whole. A percentile is a position in a ranked distribution: the 90th percentile is the value below which 90% of observations fall. A score of 90% and the 90th percentile are unrelated facts.
Why do different calculators give slightly different percentiles?
There is no single agreed definition. Excel, NumPy, and statistics packages interpolate differently at the edges. This tool uses linear interpolation on rank (n − 1)p, so results match Excel’s PERCENTILE.INC.
How many values do I need?
Percentiles are meaningful from about eight to ten observations upward. With very small samples the interpolated value sits between real observations and should be read as a rough position, not a precise cut-off.
Is the 50th percentile the median?
Yes. P50 is the median under this interpolation method. The 25th and 75th percentiles are the first and third quartiles, and their difference is the interquartile range.