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Percentile Calculator
Calculate percentile values and ranks from your data. Supports multiple calculation methods with step-by-step solutions and percentile tables.
r = (p/100) x (n+1)Results
50th Percentile
35.0000
Using exclusive method
Enter Your Data
15 numbers entered | Range: 12.00 to 65.00
Percentile Settings
Enter a value between 0 and 100
Display 5th, 10th, 25th, 50th, 75th, 90th, 95th, 99th percentiles
Result
50th Percentile Value
35.0000
50% of values are below 35.00
Rank Position
8.00
of 15
Step-by-Step Calculation
Common Percentiles Table
| Percentile | Value | Z-Score | Meaning |
|---|---|---|---|
| 5th | 12.00 | -1.51 | 5% below this value |
| 10th | 13.80 | -1.40 | 10% below this value |
| 25th (Q1) | 22.00 | -0.89 | 25% below this value |
| 50th (Median) | 35.00 | -0.09 | 50% below this value |
| 75th (Q3) | 50.00 | 0.83 | 75% below this value |
| 90th | 62.00 | 1.57 | 90% below this value |
| 95th | 65.00 | 1.75 | 95% below this value |
| 99th | 65.00 | 1.75 | 99% below this value |
Percentile Rank (Reverse Lookup)
Enter a value to find what percentile it represents in your data.
Enter a value above
Sorted Data
Highlighted value is closest to the 50th percentile (35.00)
Calculation Methods
Exclusive (R6)
r = p(n+1)/100
Excel PERCENTILE.EXC, treats data as sample
Inclusive (R7)
r = 1 + p(n-1)/100
Excel PERCENTILE.INC, most common method
Nearest Rank
r = ceil(pn/100)
No interpolation, returns actual data value
Results
50th Percentile
35.0000
?How Do You Calculate Percentile?
A percentile indicates the value below which a given percentage of data falls. To find the pth percentile: 1) Sort data in ascending order. 2) Calculate rank r = (p/100) x (n-1) + 1 (or similar formula based on method). 3) If r is a whole number, take that value. 4) If r is between integers, interpolate between adjacent values. The 50th percentile is the median.
What is a Percentile?
A percentile is a measure used in statistics indicating the value below which a given percentage of observations fall. For example, the 90th percentile means 90% of the data is below that value. Percentiles divide a data set into 100 equal parts and are commonly used in standardized testing, growth charts, and data analysis to understand relative standing within a distribution.
Key Facts About Percentiles
- Percentile shows the percentage of data below a certain value
- 50th percentile = median (middle value)
- 25th percentile = Q1 (first quartile)
- 75th percentile = Q3 (third quartile)
- Multiple calculation methods exist (exclusive, inclusive, R-style)
- Formula (exclusive): r = (p/100) x (n+1)
- Formula (inclusive): r = (p/100) x (n-1) + 1
- Percentile rank = (values below x / total values) x 100
- Z-score can be converted to percentile using normal distribution
Quick Answer
A percentile indicates the value below which a given percentage of data falls. To find the pth percentile: 1) Sort data in ascending order. 2) Calculate rank r = (p/100) x (n-1) + 1 (or similar formula based on method). 3) If r is a whole number, take that value. 4) If r is between integers, interpolate between adjacent values. The 50th percentile is the median.
Frequently Asked Questions
A percentile indicates the value below which a given percentage of observations fall. For example, if your test score is at the 90th percentile, you scored higher than 90% of test takers.
Sort your data in ascending order. Calculate the rank using r = (p/100) x (n+1) for exclusive method or r = 1 + (p/100) x (n-1) for inclusive. If r is not a whole number, interpolate between adjacent values.
Percentile rank tells you what percentage of values fall below a specific value. Formula: (count of values below x / total count) x 100. This is the inverse of finding a percentile value.
Exclusive method (R type 6) uses r = p(n+1)/100, treating data as a sample from a larger population. Inclusive method (R type 7) uses r = 1 + p(n-1)/100, treating endpoints as the full range. Results differ slightly.
Common percentiles include: 25th (Q1, first quartile), 50th (median), 75th (Q3, third quartile), 90th, 95th, and 99th. Quartiles divide data into four equal parts; deciles into ten parts.
For normally distributed data, z-scores can be converted to percentiles. z=0 is the 50th percentile (mean), z=1 is about 84th percentile, z=2 is about 98th percentile, z=-1 is about 16th percentile.
Last updated: 2025-01-15
Results
50th Percentile
35.0000
Using exclusive method