Box Plot Generator

Create box-and-whisker plots showing median, quartiles, and outliers from raw data input.

Tested tool guide Tested browser tools Checked August 16, 2026

What Box Plot Generator does, with a checked example

Box Plot Generator converts a numeric sample into a compact view of its distribution. It orders the observations, finds the median and quartiles, draws the interquartile box and whiskers, and marks values classified as outliers. This is useful for seeing spread, skew, and unusually distant observations without plotting every value individually. The main source of confusion is that quartile and whisker conventions can vary, especially for small samples, so results may differ slightly from another statistics program.

Worked example

A concrete input and expected output from the current implementation.

Input

Expected output

A box spanning 1 to 3, with the median marked at 2, whisker endpoints at 1 and 3, and no separate outlier points.

The lower quartile is 1, the median is 2, and the upper quartile is 3. Every observation lies within the displayed range, so none is separated as an outlier.

How the result is produced

Turning values into a summary

The generator treats the entered numbers as observations from one sample and orders them by value. It locates the median, then divides the ordered distribution around that center to obtain the lower and upper quartiles. Those three statistics determine the middle line and both edges of the box.

Drawing whiskers and outliers

Whiskers extend from the quartile box toward the lower and upper ends of the non-outlying data. Observations that meet the generator's outlier rule appear separately rather than extending a whisker. Because published box-plot conventions differ, whiskers should not automatically be interpreted as the sample minimum and maximum.

Good uses

Checking whether laboratory measurements are centered, skewed, or unusually dispersed.
Summarizing response times or transaction amounts when extreme observations would distort a simple range.
Creating a compact distribution graphic for a report after collecting a raw numeric sample.

Limits and checks

Quartile definitions differ, and the differences are most visible with small or even-sized samples.
An outlier marker is a rule-based flag, not proof that the observation is erroneous or should be removed.
A box plot hides ordering, clusters, gaps, and most individual values, so distinct datasets can produce the same summary.

Common questions

Does an outlier point mean that I should delete the value?

No. It means the observation falls beyond the plot's outlier boundary. The value may reflect a data-entry problem, a rare but valid event, or an important subgroup. Check the original record and the context before excluding it. The plot alone cannot determine the cause or validity of an observation.

Is the line inside the box the average?

No. The central line represents the median, which is the middle of the ordered observations. The arithmetic mean is a different statistic and can move substantially when extreme values are present. Unless the plot explicitly includes a separate mean marker, do not infer the average from the median line.

References and verification

The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.