The rule places a lower boundary 1.5 interquartile ranges below the first quartile and an upper boundary the same distance above the third quartile. The whiskers then extend to the most extreme observed values that remain within those boundaries. Observations beyond them are treated as potential outliers, so the whiskers do not necessarily end at the overall minimum and maximum.
Unequal whisker lengths indicate that the data extend different distances from the lower and upper quartiles. This imbalance can reveal asymmetry in the distribution, while a particularly extended whisker may signal greater spread on one side. Comparing the two lengths therefore adds information beyond the box itself and helps describe how the distribution extends around its middle 50%.
The interquartile range describes the width of the box, or the middle 50% of the data, whereas whisker lengths describe extension beyond each quartile toward the permitted endpoints. Using both measures separates central spread from outer spread. A data set may have a similar middle range to another but different whisker lengths, revealing a different overall pattern.
Read the lower quartile, upper quartile, and the two whisker endpoints from the plot. Subtract the lower quartile from the lower endpoint to obtain the lower whisker length. For the upper side, subtract the upper quartile from the upper endpoint. Keeping the lower and upper calculations separate preserves information about possible asymmetry.
Place the plots side by side and compare the lower and upper whisker lengths, rather than relying only on the boxes. Longer whiskers indicate that observations extend farther beyond the corresponding quartile, while unequal lengths can show different distributional shapes. This visual comparison supports concise analysis of spread and asymmetry across data sets.
Whisker lengths show how far observations extend outside the central box, which helps reveal whether data are concentrated near the middle or spread toward an endpoint. Under the 1.5-interquartile-range convention, observations beyond the whisker limits appear as potential outliers. The resulting plot links visual patterns of clustering and unusual values to numerical quartile-based limits.