Find precise percentile values from messy datasets quickly. Compare nearest-rank and interpolated methods with confidence. Visualize positions, export reports, and verify trends with ease.
| Dataset | Percentile | Nearest Rank | Interpolated |
|---|---|---|---|
| 12, 15, 18, 22, 24, 27, 31, 34, 39, 45 | P25 | 18 | 19 |
| 12, 15, 18, 22, 24, 27, 31, 34, 39, 45 | P50 | 24 | 25.5 |
| 12, 15, 18, 22, 24, 27, 31, 34, 39, 45 | P75 | 34 | 33.25 |
Sort the dataset in ascending order first. Then use one of the following percentile methods.
Nearest Rank Method r = ceil((p / 100) × n) Pp = x(r) Where: p = requested percentile n = total number of values x(r) = value at rank r in the sorted list
Linear Interpolation Method i = 1 + (p / 100) × (n - 1) Pp = x(lower) + fraction × (x(upper) - x(lower)) Where: i = fractional percentile position lower = floor(i) upper = ceil(i) fraction = i - lower
A percentile shows the value below which a chosen percentage of observations falls in a sorted dataset.
The p value is the target percentile level. For example, P90 means the 90th percentile.
Different textbooks and software use different percentile rules. This calculator lets you compare the nearest-rank result with the interpolated result.
Yes. The calculator automatically sorts your values before applying the percentile formula.
Yes. Duplicate numbers are valid and are included normally in percentile calculations.
P0 returns the minimum value, while P100 returns the maximum value in the dataset.
Interpolated methods can create values between two data points. That often gives a smoother percentile estimate.
This version is designed for raw ungrouped numbers. Grouped frequency tables need class-boundary formulas instead.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.