In large data sets, jittering the crosses helps show density

A simple dot plot is often adequate for small data sets. However in larger data sets, the crosses often overlap. Indeed, if several crosses coincide, they become indistinguishable from a single cross, so high density may be obscured.

One solution is to randomly move the crosses perpendicularly to the axis in order to separate them somewhat. This is called jittering the points.

(You should rely on a computer to do the jittering for you, but it could be done by hand by rolling a 6- or 10-sided die for each cross to determine its jittering in millimetres.)

Annual rainfall in Samaru, Nigeria

In most of Africa, agriculture is critically dependent on both the amount of rainfall and when it falls. Rainfall is however very variable and an understanding of this variability is important for planning the types of crop to grow and when to plant them.

The diagram below plots the annual rainfall (mm) in Samaru, Northern Nigeria from the years 1928 to 1983, against a horizontal axis.

Drag the slider to jitter the points. Click the button on the right to change the jittering — i.e. to change the random vertical position of the crosses.

Only enough jittering should be used to separate the high density of crosses — moving the slider about half way is best for the data above. Without jittering, too many crosses overlap to allow us to assess the distribution of values.

Note that the vertical positions of the crosses have no importance — the vertical movement of crosses is 'random' and is only intended to separate overlapping crosses.


An alternative solution to the problem of overlapping crosses will be described on the next page.