Quartile Calculator
Enter dataset values to explore quartiles, interquartile range, and related descriptive statistics using linear interpolation.
Quartiles
- Q1 (25th percentile)
- 17.2500
- Median (Q2)
- 22.5000
- Q3 (75th percentile)
- 27.7500
Count: 8
Minimum: 12.00
Maximum: 33.00
Range: 21.00
Interquartile range (IQR): 10.50
Quartile Table
| Statistic | Percentile | Value |
|---|---|---|
| Minimum | 0th percentile | 12.0000 |
| Q1 | 25th percentile | 17.2500 |
| Median (Q2) | 50th percentile | 22.5000 |
| Q3 | 75th percentile | 27.7500 |
| Maximum | 100th percentile | 33.0000 |
How to Use This Calculator
- Enter your dataset using spaces or commas to separate numbers.
- Review the quartile values and descriptive statistics shown when data is valid.
- Use the quartile table to understand where cutoff thresholds fall within your dataset.
- Apply the interquartile range to identify outliers or compare variability across datasets.
Formulas
Quartile positions use linear interpolation at 25%, 50%, and 75% of the sorted dataset: position = (n − 1) × percentile.
Interquartile range (IQR) = Q3 − Q1, a robust measure of spread resistant to outliers.
Range = maximum − minimum, highlighting the full spread of the dataset.
These formulas align with the percentile calculations used in statistical software and spreadsheet tools.
Frequently Asked Questions
Do I need to sort the data first?
No. The calculator sorts the values internally before computing quartiles.
Can quartiles handle negative numbers?
Yes. Quartiles support any numeric values, including negatives and decimals.
How many data points are required?
Quartiles work with any positive count, but interpretations are stronger with larger datasets.
How do quartiles relate to percentiles?
Q1, Q2, and Q3 correspond to the 25th, 50th, and 75th percentiles respectively.