Five Number Summary Calculator

Q: How are outliers detected using the five-number summary?

Outliers are detected using the 1.5 times IQR rule. Any value below Q1 minus 1.5 times IQR or above Q3 plus 1.5 times IQR is considered a mild outlier. Values beyond 3 times IQR from the quartiles are extreme outliers.

Calculate the five-number summary (minimum, Q1, median, Q3, maximum) for any dataset. Features an interactive box-and-whisker plot, step-by-step quartile calculations, outlier detection, and multiple calculation methods.

Free to useNo sign-up requiredUpdated Mar 2026

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About Five Number Summary Calculator

The Five Number Summary Calculator computes the five key descriptive statistics that summarize any dataset: the minimum, first quartile (Q1), median, third quartile (Q3), and maximum. This tool generates an interactive box-and-whisker plot, detects outliers automatically, and provides step-by-step calculations with three different quartile methods to match your textbook or software.

What is a Five-Number Summary?

A five-number summary is a set of five descriptive statistics that divide a dataset into four equal parts (quartiles). Together, these five values provide a comprehensive snapshot of how data is distributed, including its center, spread, and range. The five-number summary is the foundation of the box-and-whisker plot, one of the most widely used statistical visualizations.

Five-Number Summary

{Minimum, Q1, Median, Q3, Maximum}

The Five Numbers Explained

Statistic	Description	Percentile
Minimum	The smallest value in the dataset	0th percentile
Q1 (First Quartile)	The median of the lower half; 25% of data falls below this value	25th percentile
Median (Q2)	The middle value; divides the dataset in half	50th percentile
Q3 (Third Quartile)	The median of the upper half; 75% of data falls below this value	75th percentile
Maximum	The largest value in the dataset	100th percentile

How to Calculate a Five-Number Summary

Sort the data in ascending order from smallest to largest.
Find the minimum (first value) and maximum (last value).
Find the median (Q2): For an odd number of values, it is the middle value. For an even number, it is the average of the two middle values.
Find Q1: The median of the lower half of the data (values below the overall median).
Find Q3: The median of the upper half of the data (values above the overall median).

Example Calculation

Dataset: 3, 7, 8, 5, 12, 14, 21, 13, 18

Sorted: 3, 5, 7, 8, 12, 13, 14, 18, 21

Minimum = 3
Q1 = median of {3, 5, 7, 8} = (5 + 7) / 2 = 6
Median = 12 (5th value of 9)
Q3 = median of {13, 14, 18, 21} = (14 + 18) / 2 = 16
Maximum = 21

Five-Number Summary: {3, 6, 12, 16, 21}

Understanding the Box-and-Whisker Plot

A box-and-whisker plot (box plot) is the visual representation of the five-number summary:

The box spans from Q1 to Q3, representing the interquartile range (IQR) — the middle 50% of the data.
The line inside the box marks the median.
The whiskers extend from the box to the most extreme non-outlier data points.
Outlier dots are plotted individually beyond the whiskers.

Box plots are valuable for comparing distributions between groups, identifying skewness, and spotting outliers at a glance.

Quartile Calculation Methods

Different textbooks and software use different methods to calculate Q1 and Q3. This calculator supports three methods:

Method	Description	Used By
Exclusive	Excludes the median when splitting data into halves (odd n). Most common textbook method.	Most statistics textbooks, TI calculators
Inclusive	Includes the median in both halves (odd n). Also known as Tukey's hinges.	Some textbooks, certain software
Interpolation	Uses linear interpolation at the 25th and 75th percentile positions.	Excel PERCENTILE.INC, Python numpy, R default

For even-sized datasets, the exclusive and inclusive methods produce identical results. Differences appear only with odd-sized datasets.

Outlier Detection with IQR

The 1.5×IQR rule is the standard method for identifying outliers:

Outlier Fences

Lower Fence = Q1 − 1.5 × IQR | Upper Fence = Q3 + 1.5 × IQR

Mild outliers: Values between 1.5×IQR and 3×IQR from the quartiles.
Extreme outliers: Values more than 3×IQR from the quartiles.

How to Use This Calculator

Enter your data: Type or paste your numbers into the input field, separated by commas, spaces, semicolons, or new lines. You can also click a quick example to get started.
Choose a method: Select the quartile calculation method that matches your textbook or software requirements.
Click Calculate: Press the "Calculate Five-Number Summary" button to see results.
Review results: Explore the five-number summary cards, interactive box plot, method comparison, outlier analysis, step-by-step breakdown, and sorted data visualization.

Frequently Asked Questions

What is a five-number summary?

A five-number summary consists of five descriptive statistics that divide a dataset into four equal parts: the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum. It provides a concise overview of the data distribution and is the foundation for box-and-whisker plots.

What is the difference between exclusive and inclusive quartile methods?

The exclusive method (standard textbook) excludes the median from both halves when calculating Q1 and Q3. The inclusive method (Tukey's hinges) includes the median in both halves for odd-sized datasets. For even-sized datasets, both methods produce the same result. The exclusive method is more commonly taught in statistics courses.

How are outliers detected using the five-number summary?

Outliers are detected using the 1.5×IQR rule. Any value below Q1 − 1.5×IQR or above Q3 + 1.5×IQR is considered a mild outlier. Values beyond 3×IQR from the quartiles are extreme outliers. The IQR (interquartile range) is Q3 − Q1.

What is a box-and-whisker plot?

A box-and-whisker plot (box plot) is a graphical representation of the five-number summary. The box spans from Q1 to Q3, with a line at the median. Whiskers extend to the most extreme non-outlier values. Individual outlier points are plotted beyond the whiskers. It visually shows data spread, skewness, and outliers.

How do you calculate the interquartile range (IQR)?

The interquartile range (IQR) is calculated as Q3 minus Q1. It represents the spread of the middle 50% of the data. The IQR is resistant to outliers, making it a robust measure of variability compared to the range or standard deviation.

Reference this content, page, or tool as:

"Five Number Summary Calculator" at https://MiniWebtool.com/five-number-summary-calculator/ from MiniWebtool, https://MiniWebtool.com/

by miniwebtool team. Updated: Mar 21, 2026

Developer API available: Run this tool from your app, automation, or agent with one JSON HTTP request. View API docs

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