Box Plot
Updated 2026-08-13
INTRODUCTION
English translation pending.
CORE DEFINITION
A box plot represents a distribution using a box spanning the first to third quartiles, a line at the median, whiskers extending to the most extreme values within a defined range, and individually plotted points for values beyond that range. Its core proposition is that the shape of the box and the position of the median within it reveal skew and spread, while whisker length and outlier points flag unusual observations, all within a space small enough to place many distributions side by side. The key qualification is that the graphic hides the underlying sample size and the detailed shape of the distribution, so bimodal or heavily skewed data can look deceptively ordinary.
SCAFFOLDING EFFECT
Reduce cognitive load
- Group comparison: place several box plots side by side to compare medians and spread at a glance. - Outlier flag: use points beyond the whiskers as a starting list for investigation. - Skew read: check whether the median sits off-center in the box to detect asymmetry.
Anchor fast decisions
Quartiles summarize a distribution with a few robust statistics that are insensitive to extreme values, so the box and whiskers describe the bulk of the data while outliers are shown separately. Compressing each distribution into the same small footprint makes differences between groups visible that a table of summary numbers would obscure.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Box_plotverified
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