Box Plot

The Box Plot tool provides a way of illustrating the spread of data points for variables and allows us to perform side-by-side comparisons with other observations. The element of the box in the plot shows:

  • The range (minimum and maximum values).
  • The measure of central tendency (the median).
  • The distribution symmetry (how the data are distributed around the upper and lower quartiles).

It is usually used to compare several sets of observations or data. The box plot is oriented in a way that each whisker (which represents the minimum and maximum of the values) are vertical and each box represents the first quartile (bottom horizontal line) and the third quartile (top horizontal line) of the values. In addition, the median is represented by a horizontal thick line across the box.


For this worked example, we will compare the First Party Preference by Polling Place results with respect to minor parties in the 2019 Federal Election throughout the Greater Perth area.

Select the Greater Perth GCCSA as your area.

Select AEC – Federal Election – First Party Preference by Polling place (Point) 2019 as your dataset, with the following variables:

  • Polling Place ID
  • Independent Ordinary Votes
  • Pauline Hanson’s One Nation Ordinary Votes
  • The Greens (Wa) Ordinary Votes
  • United Australia Party Ordinary Votes
  • Geometry (if you would like to visualise polling places)


Once you have set up your data, open the Box Plot tool (Tools → Charts → Box Plot). The input fields are as follows:

  • Dataset Input: The dataset containing the variables you would like to test. Select AEC – Federal Election – First Party Preference by Polling place (Point) 2019
  • Variable: The variables we would like to compare:
    • Select Independent Ordinary Votes.
    • Select Pauline Hanson’s One Nation Ordinary Votes.
    • Select The Greens (Wa) Ordinary Votes.
    • Select United Australia Party Ordinary Votes.
  • Use Variable Titles: Check this box to use the variable’s names instead of the IDs on your output chart.
  • Chart Title: Title for the plot to display. In this instance, we have chosen Minor Party voting in Greater Perth GCCSA in the 2019 federal election.
  • Show Gridlines: Select this if you want to choose grid-lines for your graph. Tick this box.
  • Greyscale: Select this if you want your graph to be in greyscale, rather than in the default colour. Untick this box.

The input parameters are summarised in the image below, once complete click Run Tool.


Once the tool has run, click the Display button on the pop-up dialogue box that appears.

Your output should look something like the graph below. This indicates that the median amount of votes for The Greens (Wa) was higher than all three other groups. However, the range in voting count for Pauline Hanson’s One Nation was higher.

Dewey, M. E. (1992). Algorithm AS 272: Box Plots. Journal of the Royal Statistical Society. Series C (Applied Statistics), 41(1), 274–284.
Dodge, Y. (2008). Box Plot. In The concise encyclopedia of statistics (pp. 55–57). Springer Science & Business Media.
Salkind, N. J. (2010). Box Plot. In Encyclopedia of research design (Vol. 1, pp. 105–109). Sage.
Venables, W. N., Smith, D. M., & Team, R. C. (1999). An introduction to R: Notes on R: A programming environment for data analysis and graphics Version 3.1. 0 (2014-04-10). R Core Team.

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