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Statistics · Descriptive

Five-Number Summary

Paste a dataset for the min, Q1, median, Q3, and max — plus the IQR, outliers, and a box plot.

Separate values with commas, spaces, or new lines. Non-numeric entries are ignored.
Sample data — tap to load
4
Minimum
8
Q1 (25%)
15.5
Median (50%)
23
Q3 (75%)
42
Maximum
15
IQR (Q3 − Q1)
Outliers (beyond Q1 − 1.5 × IQR or Q3 + 1.5 × IQR)
None
Fences: lower -14.5, upper 45.5.
Box plot
Box plot of the dataset4815.52342

The box spans Q1 to Q3, the thick line is the median, whiskers reach the most extreme values inside the fences, and any dots are outliers.

Quartiles use the median-of-halves (Tukey) method, so results may differ slightly from calculators that use the exclusive or inclusive interpolation methods.

The five-number summary is the minimum, first quartile (Q1), median, third quartile (Q3), and maximum of a sorted dataset. For 4, 8, 15, 16, 23, 42 it is min 4, Q1 8, median 15.5, Q3 23, max 42, giving an IQR of 15. A box plot draws these five numbers so you can read the spread at a glance.

What the five numbers describe

The five-number summary compresses a whole dataset into five landmarks that mark how the values are spread out. The minimum and maximum give the full range. The median is the middle value, splitting the data into a lower and upper half. The first quartile (Q1) sits a quarter of the way in and the third quartile (Q3) three-quarters of the way in, so the box between them holds the middle 50% of the data. The width of that box, Q3 − Q1, is the interquartile range (IQR) — a measure of spread that ignores the extremes.

How the quartiles are computed

This tool uses the median-of-halves method, often called the Tukey method. First sort the data and find the median. Then split the sorted values into a lower half and an upper half at the median — when the count is odd, the middle value belongs to neither half and is left out. Q1 is the median of the lower half and Q3 is the median of the upper half. The outlier fences follow the standard rule: anything below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR is flagged as an outlier.

Worked example

Six values: 4, 8, 15, 16, 23, 42.

  1. 1
    Sort the data and read off the ends. Sorted: 4, 8, 15, 16, 23, 42. The minimum is 4 and the maximum is 42.
  2. 2
    Find the median. With 6 values the two middle ones are 15 and 16, so the median is (15 + 16) ÷ 2 = 15.5.
  3. 3
    Take the median of the lower half for Q1. The lower half is 4, 8, 15, whose middle value is 8, so Q1 = 8.
  4. 4
    Take the median of the upper half for Q3. The upper half is 16, 23, 42, whose middle value is 23, so Q3 = 23.
  5. 5
    Compute the IQR and check for outliers. IQR = 23 − 8 = 15. Fences are 8 − 1.5 × 15 = −14.5 and 23 + 1.5 × 15 = 45.5, so no value is an outlier.

What each number means

The five landmarks plus the spread and outlier rule.

StatisticWhat it marksHow it is found
MinimumSmallest valueFirst value after sorting
Q1 (25th percentile)Quarter of the way through the dataMedian of the lower half
Median (50th percentile)Middle of the dataMiddle value (or mean of the two middle values)
Q3 (75th percentile)Three-quarters through the dataMedian of the upper half
MaximumLargest valueLast value after sorting
IQRSpread of the middle 50%Q3 − Q1
OutlierUnusually extreme valueBelow Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR

Reading the box plot

The box is the middle half of the data. Its left edge is Q1, its right edge is Q3, and the line inside it is the median. A wide box means the central values are spread out; a narrow box means they are tightly packed. If the median sits off-centre inside the box, the data is skewed toward the longer side.

The whiskers and dots show the tails. The whiskers reach the most extreme values that still fall inside the fences, and any point plotted beyond them is a flagged outlier. Because the quartiles resist extreme values, the box and median stay stable even when a few points are far out.

Quartile methods differ. This calculator uses the Tukey median-of-halves method; other tools use the exclusive or inclusive interpolation methods, so Q1 and Q3 (and therefore the fences) can differ slightly for the same data. The minimum, maximum, and median never change between methods.

How are the quartiles calculated?
This tool uses the Tukey median-of-halves method. The median splits the sorted data into a lower and an upper half; Q1 is the median of the lower half and Q3 is the median of the upper half. When the count is odd, the overall median is excluded from both halves.
What makes a value an outlier?
A value is flagged as an outlier when it falls below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR. These two limits are the lower and upper fences, and any point outside them is drawn as a separate dot on the box plot.
Why do my quartiles differ from another calculator?
Quartile methods vary. Besides the Tukey method used here, spreadsheets and statistics packages may use exclusive or inclusive interpolation (for example Excel’s QUARTILE.EXC and QUARTILE.INC), which can shift Q1 and Q3 slightly. The min, median, and max are the same across methods.
What is the difference between the range and the IQR?
The range is max − min, so it depends entirely on the two most extreme values. The IQR is Q3 − Q1, the width of the middle 50% of the data, so it ignores the tails and is far less sensitive to outliers.
How does the box plot handle whiskers?
Each whisker extends to the most extreme data value that is still inside the fences — not necessarily to the raw minimum or maximum. If the smallest or largest value is an outlier, the whisker stops at the nearest non-outlier and the extreme value is drawn as a dot.
How many data points do I need?
You need at least two values to split the data into halves and compute Q1 and Q3. More points give a more meaningful summary; with very few values the quartiles can coincide with the min, median, or max.