No Results
No results found for your search. Please try another term.
Online Percentile Calculator
Calculate percentiles accurately with our online percentile calculator. Use your dataset to find the value below which a specific percentage of data falls. Ideal for performance ranking and statistical analysis.
Answer
10.55
| Percentile Position | Value | Percentile Position | Value | Percentile Position | Value |
|---|---|---|---|---|---|
| 0 | 2 | 45 | 23 | 90 | 96.8 |
| 5 | 4.8 | 50 | 23 | 95 | 165.4 |
| 10 | 7.6 | 55 | 23 | 100 | 234 |
| 15 | 10.55 | 60 | 26 | ||
| 20 | 14.4 | 65 | 31.25 | ||
| 25 | 18.25 | 70 | 36.5 | ||
| 30 | 21.2 | 75 | 38 | ||
| 35 | 21.9 | 80 | 38 | ||
| 40 | 22.6 | 85 | 38 |
Oops! Something went wrong. Please try again.
What Is This Tool?
This percentile calculator helps determine the value below which a given percentage of data points fall. It processes a sorted dataset and the desired percentile to provide an accurate percentile value using numeric sorting and linear interpolation.
How to Use This Tool?
- Enter your dataset as a list of numbers sorted in ascending order
- Specify the desired percentile (P) between 0 and 100
- Click the calculate button to compute the percentile value
- Review the result, which shows the position and interpolated value
Key Features
- Calculates percentile values from sorted numerical data
- Uses a standard formula for percentile position: (P/100) × (N + 1)
- Supports percentile values between 0 and 100
- Provides precise results through linear interpolation
- Easy-to-use interface for quick calculations
- Browser-based tool requiring no installation
Examples
- Given data 5, 8, 12, 20, 25, find the 40th percentile:
- - Sorted data: 5, 8, 12, 20, 25
- - Number of points (N): 5
- - Rank calculation: (40/100) × (5 + 1) = 2.4
- - The rank lies between the 2nd (8) and 3rd (12) values
- - Interpolated percentile value: 8 + 0.4 × (12 − 8) = 9.6
Common Use Cases
- Assessing student performance in standardized testing
- Analyzing comparative scores across groups
- Evaluating statistical distributions in data analytics
- Ranking performance metrics in research studies
- Modeling data for distribution and percentile-based reports
Tips & Best Practices
- Always provide a sorted dataset for accurate calculations
- Use consistent percentile definitions for comparisons
- Double-check entered data values to avoid input errors
- Understand that slight variations may occur due to calculation methods
- Use the calculator to complement domain-specific analysis
Limitations
- Results depend on the specific percentile calculation method used
- Nearest-rank and other interpolation methods can produce varying outputs
- This tool applies a single standard approach and may differ slightly from others
- Accuracy depends on data quality and sorting
- Not suitable for datasets without numeric values or improper formatting
Frequently Asked Questions
- What is the formula for calculating percentile position?
- The formula is Percentile position (Rank) = (P/100) × (N + 1), where P is the desired percentile and N is the number of data points.
- Do I need to sort my data before using this calculator?
- Yes, sorting your data in ascending order is essential for accurate percentile calculations.
- Can this calculator handle percentiles outside 0 to 100?
- No, the percentile value must be between 0 and 100 for valid results.
- Why might results vary between different percentile calculators?
- Different calculators may use various percentile calculation methods, leading to slight differences in results.
- Is interpolation used to find the final percentile value?
- Yes, linear interpolation is applied when the rank falls between two data points to provide precise values.
Key Terminology
- Percentile
- A value below which a specified percentage of data points in a dataset fall.
- Rank (Percentile Position)
- The calculated position within a sorted dataset corresponding to the desired percentile.
- Linear Interpolation
- A method to estimate values between two known data points linearly.
- Sorted Dataset
- A list of numerical data organized in ascending order.
- P (Percentile)
- The desired percentile, expressed as a percentage between 0 and 100.
- N (Number of Data Points)
- The total count of data values in the dataset.