Percentile Calculator

A percentile indicates the value below which a given percentage of observations in a dataset fall. For example, the 75th percentile is the value below which 75% of the data points lie. It is calculated by sorting the dataset and applying either the nearest rank or linear interpolation method to find the corresponding value.

The inclusive (nearest rank) method finds the value at the position given by ceiling(k/100 × n), where n is the number of data points. The exclusive (linear interpolation) method interpolates between the two surrounding values for a more precise result. For large datasets the difference is minimal, but for small datasets the two methods can give noticeably different answers.

Being in the 90th percentile for height means the child is taller than 90% of children of the same age and sex. It does not mean anything is wrong — growth charts show a wide range of normal. What matters most is that a child grows consistently along their own curve over time, as assessed by their pediatrician.

Not necessarily. Whether a higher percentile is desirable depends entirely on what is being measured. For test scores, a higher percentile rank is better. For blood pressure or body weight, a very high percentile may indicate a concern. Percentiles simply show where a value sits relative to the rest of the dataset.

The IQR is the difference between the 75th percentile (Q3) and the 25th percentile (Q1). It represents the middle 50% of the data and is a robust measure of spread that is not affected by extreme outliers. A larger IQR indicates more variability in the central portion of the dataset.

While this calculator works with any number of values, percentile estimates become more meaningful and stable with larger datasets. With very small datasets (fewer than 10 values), percentile calculations can be sensitive to the method used and individual data points. For statistical work, at least 30 data points are generally recommended.

This calculator computes percentiles from any dataset you provide. For standardized baby growth percentiles (weight, height, head circumference by age and sex), specialized growth charts from the CDC or WHO are typically used, as those compare against large reference populations. This tool is best suited for custom datasets where you have all the raw values available.

A percentage is a proportion expressed out of 100 (e.g., you scored 80% on a test). A percentile is a rank that tells you how your value compares to others in a dataset (e.g., you scored in the 80th percentile, meaning you scored higher than 80% of test-takers). A score of 80% could correspond to many different percentile ranks depending on how everyone else performed.