Strip plots

Like histograms, strip plots show the distribution of a measure – that is, the number of measurements recorded for each unit of a continuous measure (eg height or blood pressure).

This section covers:

Using strip plots

In a strip plot, each measurement or piece of data is shown as a dot or point along the distribution’s axis. If multiple data points are recorded for the same value on the distribution, these points can be stacked on top of each other (also called ‘jittering’). Alternatively, data points can be shown in various (colour) densities, so that darker areas of the distribution indicate a clustering of data points:

Strip plots showing the distribution of the age that surveyed men and women started smoking.

Strip plots are typically used to display single distributions. However, this kind of graph can also be used to plot multiple distributions of the same measure for several groups or categories (eg blood pressure distributions for men with 5 different medical conditions). Multiple distributions are plotted side by side against the same y axis. Leave white space between the strips (a ratio of white space to strip plot of approximately 1:1) to make it clear to the reader that the distributions are for different groups or time points.

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Alternatives to strip plots

Strip plots are most useful for displaying the distribution of a small dataset that has few instances of multiple data points on the same value of the distribution. However, this kind of graph is not commonly used in many settings and may be unfamiliar to your readers. Distribution data can also be shown using box plots; however, box plots are also uncommon in many disciplines.

Tip. Consider using a simple histogram to display a single-distribution dataset – particularly if your dataset includes multiple data points for the same value on a distribution. For multiple distributions, consider using a frequency polygon.
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