Quartile Calculator - Q1, Q2, Q3, IQR
Calculate quartiles (Q1, Q2, Q3), interquartile range (IQR), and five-number summary. Identify outliers with our quartile calculator.
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At least 4 numbers required for quartile calculation
Quartiles divide a ranked dataset into four equal parts. They help understand the distribution and spread of data.
- Q1 (First Quartile): 25th percentile - 25% of data falls below this value
- Q2 (Second Quartile): 50th percentile / Median - middle value of the dataset
- Q3 (Third Quartile): 75th percentile - 75% of data falls below this value
IQR = Q3 - Q1. It represents the range of the middle 50% of your data and is a robust measure of spread that isn't affected by outliers.
The five-number summary (Min, Q1, Q2, Q3, Max) provides a complete picture of your data's distribution and is the basis for box plots.
The 1.5 × IQR rule identifies potential outliers. Values more than 1.5 times the IQR below Q1 or above Q3 are considered outliers.
How to Use Quartile Calculator
- 1
Enter at least 4 numbers separated by commas, spaces, or new lines.
- 2
Click "Calculate Quartiles" to compute the result.
- 3
View Q1 (25th), Q2 (50th/median), Q3 (75th percentiles).
- 4
See IQR, five-number summary, and outlier bounds.
Frequently Asked Questions
What are quartiles?▾
Quartiles divide a ranked dataset into four equal parts. Q1 (25th percentile), Q2 (median/50th), and Q3 (75th percentile) help understand data distribution.
What is IQR?▾
Interquartile Range (IQR) = Q3 - Q1. It represents the range of the middle 50% of data and is a robust measure of spread not affected by outliers.
How are outliers detected?▾
The 1.5 × IQR rule identifies potential outliers. Values more than 1.5 times the IQR below Q1 or above Q3 are considered outliers.
What is a five-number summary?▾
The five-number summary (Min, Q1, Q2, Q3, Max) provides a complete picture of data distribution and is the basis for box plots.
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