Interquartile Range Calculator

Calculate the interquartile range (IQR), quartiles Q1, Q2, Q3, five-number summary, and detect outliers with interactive box plot visualization and step-by-step calculations.

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Quartile Method

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Enter at least 4 numbers. If your text has non-numeric content, use our Number Extractor first.

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About Interquartile Range Calculator

The Interquartile Range Calculator computes the IQR, all quartiles (Q1, Q2, Q3), five-number summary, and automatically detects outliers in your dataset. With an interactive box plot visualization and step-by-step calculations, this tool helps you understand the spread and distribution of your data.

What is the Interquartile Range (IQR)?

The Interquartile Range (IQR) is a measure of statistical dispersion that represents the spread of the middle 50% of your data. It is calculated as the difference between the third quartile (Q3) and the first quartile (Q1):

Interquartile Range Formula

$$IQR = Q_3 - Q_1$$

Unlike the range (max - min), the IQR is resistant to outliers, making it a more robust measure of variability. It is widely used in descriptive statistics, data analysis, and for identifying outliers through the 1.5×IQR rule.

Understanding Quartiles

Quartiles divide a sorted dataset into four equal parts:

Q1 (First Quartile / 25th Percentile): The value below which 25% of the data falls. Also called the lower quartile.
Q2 (Second Quartile / Median / 50th Percentile): The middle value of the dataset, dividing it into two equal halves.
Q3 (Third Quartile / 75th Percentile): The value below which 75% of the data falls. Also called the upper quartile.

Five-Number Summary

The five-number summary provides a quick overview of a dataset's distribution:

Minimum: The smallest value
Q1: First quartile (25th percentile)
Q2: Median (50th percentile)
Q3: Third quartile (75th percentile)
Maximum: The largest value

These five values are used to construct a box plot (box-and-whisker plot), which visually displays data distribution, skewness, and outliers.

Outlier Detection: The 1.5×IQR Rule

The IQR is commonly used to identify outliers using fences:

Outlier Fences

$$\text{Lower Fence} = Q_1 - 1.5 \times IQR$$ $$\text{Upper Fence} = Q_3 + 1.5 \times IQR$$

Data points falling below the lower fence or above the upper fence are considered potential outliers. For extreme outliers, the 3×IQR rule is used (values beyond Q1 - 3×IQR or Q3 + 3×IQR).

Quartile Calculation Methods

There are different methods for calculating quartiles, which may produce slightly different results:

Method	Used By	Description
Exclusive	TI-83/84, Moore & McCabe, Excel QUARTILE.EXC	Excludes the median when calculating Q1 and Q3 for odd n. Most common in education.
Inclusive	TI-85, Minitab, Excel QUARTILE.INC	Includes the median in both halves when calculating Q1 and Q3 for odd n.

This calculator supports both methods. The Exclusive method is more commonly taught in statistics courses and is the default.

How to Use This Calculator

Enter your data: Input numbers separated by commas, spaces, or line breaks. You need at least 4 values.
Select quartile method: Choose Exclusive (default, most common) or Inclusive based on your requirements.
Set decimal precision: Select 2-15 decimal places for your results.
Calculate: Click the button to see IQR, quartiles, five-number summary, outlier detection, box plot, and step-by-step calculations.

Applications of IQR

Data Analysis: Understanding the spread and variability of datasets
Quality Control: Monitoring process variability in manufacturing
Outlier Detection: Identifying unusual values that may need investigation
Box Plots: Creating visual representations of data distribution
Comparing Distributions: Assessing variability across different groups
Research & Statistics: Reporting measures of dispersion in scientific studies

IQR vs Other Measures of Spread

Measure	Sensitivity to Outliers	Best Used When
IQR	Resistant (robust)	Data may contain outliers; you want to describe typical spread
Range	Very sensitive	Quick overview; no outliers present
Standard Deviation	Sensitive	Data is normally distributed; need precise variability measure
Variance	Sensitive	Statistical calculations requiring squared deviations

Frequently Asked Questions

What is the Interquartile Range (IQR)?

The Interquartile Range (IQR) is a measure of statistical dispersion equal to the difference between the third quartile (Q3) and first quartile (Q1). It represents the spread of the middle 50% of your data and is calculated as IQR = Q3 - Q1. The IQR is resistant to outliers, making it a robust measure of variability.

How do you calculate the IQR?

To calculate the IQR: 1) Sort your data in ascending order. 2) Find Q1 (the median of the lower half). 3) Find Q3 (the median of the upper half). 4) Calculate IQR = Q3 - Q1. The result represents the range containing the middle 50% of your data.

What is the 1.5 IQR rule for outliers?

The 1.5 IQR rule identifies outliers as data points that fall below Q1 - 1.5×IQR (lower fence) or above Q3 + 1.5×IQR (upper fence). Points beyond these boundaries are considered potential outliers. The 3×IQR rule identifies extreme outliers.

What is the difference between Exclusive and Inclusive quartile methods?

The Exclusive method (used by TI-83/84, Moore & McCabe) excludes the median when calculating Q1 and Q3 for odd-sized datasets. The Inclusive method (used by TI-85, Minitab) includes the median in both halves. Both are valid; the Exclusive method is more common in education.

What is the five-number summary?

The five-number summary consists of: Minimum, Q1 (first quartile), Q2 (median), Q3 (third quartile), and Maximum. These five values provide a quick overview of your data's distribution and are used to construct box plots.

Why is IQR preferred over range for measuring spread?

IQR is preferred because it is resistant to outliers. The range (max - min) can be heavily influenced by extreme values, while IQR focuses on the middle 50% of data. This makes IQR a more robust and reliable measure of typical variability in a dataset.

Additional Resources

Reference this content, page, or tool as:

"Interquartile Range Calculator" at https://MiniWebtool.com/interquartile-range-calculator/ from MiniWebtool, https://MiniWebtool.com/

by miniwebtool team. Updated: Jan 27, 2026

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About Interquartile Range Calculator

What is the Interquartile Range (IQR)?

Understanding Quartiles

Five-Number Summary

Outlier Detection: The 1.5×IQR Rule

Quartile Calculation Methods

How to Use This Calculator

Applications of IQR

IQR vs Other Measures of Spread

Frequently Asked Questions

What is the Interquartile Range (IQR)?

How do you calculate the IQR?

What is the 1.5 IQR rule for outliers?

What is the difference between Exclusive and Inclusive quartile methods?

What is the five-number summary?

Why is IQR preferred over range for measuring spread?

Additional Resources

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