Find any percentile value or rank a score in your dataset instantly
Dataset
10 values parsed · min 12 · max 95
Find Value at Percentile
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Result
Common Percentiles Summary
| Percentile | Value | Label |
|---|---|---|
| 10th | 19.2 | 10th percentile (P10) |
| 25th | 36.25 | 1st quartile (Q1) |
| 50th | 52.5 | Median (Q2) |
| 75th | 69 | 3rd quartile (Q3) |
| 90th | 86 | 90th percentile (P90) |
| 95th | 90.5 | 95th percentile (P95) |
| 99th | 94.1 | 99th percentile (P99) |
Sorted Dataset
How It Works
A percentile calculator helps you make sense of data distributions — whether you need to find the value at the 90th percentile of a dataset, calculate Q1/Q2/Q3 quartiles, or determine what percentile rank a specific score falls at. Enter any list of numbers and this free tool computes results instantly using standard linear interpolation, the same method used by Excel and NumPy.
It uses linear interpolation (also called the inclusive method), identical to Excel's PERCENTILE.INC and NumPy's default. The index is calculated as (P/100) × (n−1), then the result is interpolated between the two adjacent sorted values. This is the most widely accepted method in statistics.
The exclusive rank is (count of values strictly below your value ÷ n) × 100. The inclusive rank is (count of values ≤ your value ÷ n) × 100. The exclusive method is common in standardized testing and education; the inclusive version is used when you want ties to count toward the rank.
Quartiles divide a sorted dataset into four equal parts. Q1 is the 25th percentile, Q2 (the median) is the 50th percentile, and Q3 is the 75th percentile. This calculator shows all common quartiles in the summary table automatically.
Yes. The calculator accepts any finite number — integers, decimals, and negatives — separated by commas, spaces, or newlines. Invalid tokens (like letters) are flagged with a friendly error message so you can correct them before calculating.