Title: Visualising ranges and extreme values: boxplots
Course: UGQuants (SSPS) > Section: Univariate Analysis

Visualising ranges and extreme values: boxplots

A boxplot is a useful way of representing data from interval or ratio level variables through highlighting the range of the data as well as any extreme values.

Boxplots may be displayed horizontally or vertically. The example below is a vertical boxplot. It represents the distribution of data from the variable showing the % of female representatives in the national parliaments of 183 countries, taken from the WDI 2011 dataset.

Sometimes they simply reflect an error in the data, and are often worth checking on this basis. For example, if we have attributed a value of 190 for someone’s age in years, the most likely explanation is that we have mistyped an additional 0 by mistake when recording the data.

 | Outliers are often significant in quantitative data analysis for a number of reasons:
 | Sometimes they simply reflect an error in the data, and are often worth checking on this basis. For example, if we have attributed a value of 190 for someone’s age in years, the most likely explanation is that we have mistyped an additional 0 by mistake when recording the data
 | Assuming they are not errors, they offer us potentially theoretically-interesting puzzles: why does this case or cases appear to be so distinctive for this particular variable? Can we reconcile this with our more general explanations or theories about our data?
 | When we are trying to model or ‘fit’ data, even one extreme value might have a large effect on our model or fit. This might lead us to consider if a better model of our data might be provided if we exclude outliers, although we should always be transparent about this and explain why such exclusion is justified.