Statistics & Probability

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Percentile Rank Calculator.

Calculate the midrank percentile of a value within a data set.

On-device calculationNo signup
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Set your values

Results update as you type.

percentileRank: 70

percentileRank

70.000000
lessCount: 3

lessCount

3.000000
equalCount: 1

equalCount

1.000000

Results update automatically as you type.

Use Cases

Compare test scores

Determine how a student's test score ranks relative to the class or a larger group.

Example: If a score of 85 is in the 90th percentile, it means the student scored higher than 90% of test takers.

Analyze income distribution

See where a particular income falls in a sample of household incomes.

Example: An income of $75,000 might be at the 60th percentile in a given dataset.

Frequently Asked Questions

What is a percentile rank?
A percentile rank indicates the percentage of scores in a dataset that fall below a given value. For example, a percentile rank of 80 means the value is higher than 80% of the data.
How is the midrank percentile calculated?
The midrank method averages the ranks of tied values. For each value, count how many data points are less than it, add half the number of tied values, then divide by the total number of data points and multiply by 100.
What does the 'Value' field represent?
The 'Value' field is the specific number you want to find the percentile rank for within your list of data values. It should be a number that may or may not be present in the dataset.

Tips & Common Mistakes

Tips

  • Ensure all data values are entered correctly, separated by commas or spaces, to avoid calculation errors.
  • The target value does not need to be one of the data values; the calculator will still compute its percentile rank.
  • For large datasets, double-check that you have included all relevant data points to get an accurate percentile.
  • Remember that percentile ranks are relative to the dataset you provide; changing the dataset changes the rank.

Common Mistakes to Avoid

  • Entering the target value as part of the data values, which can skew the percentile calculation.
  • Using inconsistent separators (e.g., mixing commas and spaces) which may cause parsing errors.
  • Confusing percentile with percentage: a percentile rank is not the same as a percentage score.

Last updated: August 13, 2026