Percentile Rank Calculator
Compute the percentile rank of any score. Use Normal Distribution mode for standardized tests or From Count mode when you know how many scored above and below.
🎯 What is Percentile Rank?
Percentile rank is the percentage of scores in a reference distribution that fall at or below a given score. If your percentile rank on an IQ test is 84, it means 84% of the population scored at or below your level. It is one of the most widely used statistics in education, psychology, and hiring because it converts a raw number into a meaningful relative standing: regardless of the original scale, a percentile rank of 90 always means you outperformed 90% of the comparison group.
There are two main situations where you need a percentile rank. The first is when you know the population parameters. Standardized tests such as IQ assessments (mean 100, SD 15), the SAT (mean roughly 1010, SD roughly 211), the GRE Quantitative section (mean 153, SD 9.4), or height and weight charts are designed with published means and standard deviations. If the underlying distribution is approximately normal, the formula is: PR = Phi((score - mean) / SD) times 100, where Phi is the standard normal CDF. The second situation is when you have raw data or a class rank. Here the empirical formula applies: PR = ((number of values below your score + 0.5 times number equal to your score) / total count) times 100.
A common confusion is between percentile rank and percentage score. Scoring 75% on an exam is a raw score; it tells you nothing about how you compared to others. If the exam was very hard and most students scored below 60%, your 75% might be at the 92nd percentile. If the exam was easy and most scored above 80%, your 75% might be at the 20th percentile. Percentile ranks remove the scale and focus entirely on relative standing.
Another distinction worth knowing is between percentile rank and percentile (or percentile point). The 90th percentile is a score: it is the value below which 90% of the distribution falls. The percentile rank is the reverse: given a score, it finds which percentile the score corresponds to. If the 90th percentile is a score of 1350, then a student scoring exactly 1350 has a percentile rank of 90. This calculator goes from score to rank; to go from rank to score, use the Percentile Calculator.
📐 Formula
📖 How to Use This Calculator
Steps
💡 Example Calculations
Example 1 - IQ Score Percentile (Normal Distribution Mode)
IQ score of 125, WAIS-IV scale (mean = 100, SD = 15)
Example 2 - Class Rank (From Count Mode)
A student's exam score tied with 3 others; 42 students scored lower in a class of 60
Example 3 - SAT Score Comparison (Normal Distribution Mode)
SAT score of 1350 (2024 approximate national norms: mean = 1028, SD = 210)
❓ Frequently Asked Questions
🔗 Related Calculators
What is percentile rank in statistics?
Percentile rank is the percentage of scores in a distribution that fall at or below a given score. If your percentile rank is 82, then 82% of scores in the reference group are at or below your score. It is different from a percentage score: a percentile rank of 82 does not mean you answered 82% of questions correctly.
What is the formula for percentile rank?
The midpoint formula: PR = ((L + 0.5 x E) / N) x 100, where L is the number of values below your score, E is the number of values equal to your score, and N is the total count. For normal distributions, PR = Phi(z) x 100 where z = (score - mean) / SD and Phi is the standard normal CDF. The normal formula is exact for normally distributed data.
How do you find percentile rank from a z-score?
Percentile rank = Normal CDF(z) x 100. For z = 1.0, the CDF is 0.8413, so the percentile rank is 84.13%. For z = -1.0, it is 15.87%. For z = 0, it is exactly 50%. This tells you what proportion of a standard normal distribution falls below the given z-score.
What is the difference between percentile rank and percentile?
A percentile is a value in a distribution: the 90th percentile is the score below which 90% of observations fall. Percentile rank is a rank: it tells you what percent of the distribution is at or below your specific score. They are inverses of each other: if your score of 85 is the 90th percentile, your percentile rank is 90.
How do you calculate percentile rank from rank position in a class?
If you ranked 10th in a class of 50 (with rank 1 = lowest), then 9 students scored below you and 1 scored the same (if the ranks are consecutive). Using the midpoint formula: PR = (9 + 0.5) / 50 x 100 = 19%. If rank 1 = highest, then 40 students scored below you: PR = 40 / 50 x 100 = 80%.
What percentile rank is considered average?
Percentile ranks from 25 to 75 are typically described as average. A percentile rank of 50 is the exact median. Above 75 is above average; above 90 is high; above 98 is exceptional. Below 25 is below average; below 10 is low; below 2 is exceptionally low. These categories are used in psychometric testing and educational measurement.
How do you find percentile rank for IQ scores?
IQ tests follow a normal distribution with mean = 100 and SD = 15. Use the formula: z = (IQ - 100) / 15, then PR = Phi(z) x 100. IQ of 115: z = 1.0, PR = 84.1%. IQ of 130: z = 2.0, PR = 97.7%. IQ of 85: z = -1.0, PR = 15.9%. Enter these values in the Normal Distribution mode with mean = 100 and SD = 15.
What is the difference between percentile rank and raw score?
A raw score is the actual number of points or correct answers. A percentile rank converts that raw score into a relative standing within a group. Two students with the same raw score of 75/100 can have very different percentile ranks depending on whether the test was easy (most scored higher, so PR is low) or hard (most scored lower, so PR is high).
How is percentile rank used in standardized testing?
Percentile ranks allow comparison across test takers regardless of the specific scale. College entrance exams like the SAT report both the scaled score and the percentile rank so applicants know how they compare nationally. A 1400 SAT score was at the 94th percentile in 2024, meaning 94% of test takers scored at or below that level. Percentile ranks are more interpretable than raw scores for admissions decisions.
Can percentile rank be greater than 100 or less than 0?
No. Percentile rank is always between 0 and 100 because it is a percentage. A score equal to the maximum in a dataset has a percentile rank just below 100 (not exactly 100, because the score itself is included in the denominator). Technically, percentile ranks range from 1/2N x 100 (minimum) to (N - 1/2) / N x 100 (maximum) when using the midpoint formula.
What is the difference between percentile rank and standard score?
A standard score (z-score, T-score, stanine) is a linear transformation of the raw score using the mean and SD. A percentile rank is a nonlinear transformation that maps a score to its rank in the distribution. For normal distributions, PR = Phi(z) x 100. For non-normal distributions, the mapping is different. T-score = 50 + 10z always maps to PR = 50 when T = 50, regardless of the distribution shape.
How accurate is the normal distribution approximation for percentile rank?
The normal distribution model is highly accurate when the underlying data is approximately normally distributed, which holds for many standardized tests, heights, and biological measurements. It is less accurate for skewed data (income, response times, test pass rates) or bimodal distributions. For raw data that may not be normal, use the From Count mode to get an exact empirical percentile rank.