Training your critical eye
Be aware that many data visualisations can be misleading – always take a critical view. Do the segments of a pie chart actually add up to 100%? Are the segments proportionate? Do the horizontal and vertical axes of a bar chart make sense? See viz.wtf for examples of bizarre, funny and downright wrong data visualisations.
Some data visualisations may be unintentionally misleading, but be alert to graphics which lead you to a conclusion that support specific agendas. For example, this graph was tweeted by Ann Coulter, a far-right US media pundit, to support the idea that the impact of COVID-19 had been overstated.
However the graph was misread as the journalist who explored the original figures, Andy Kiersz, wrote in his article. For a start, the two visualisations show different age categories; they also compare two data sets without additional context – such as the fact that the US and South Korea have taken very different approaches to managing the coronavirus outbreak. Finally, the figures don’t support the assertion made in the tweet: the death rate for South Koreans under 60 for COVID-19 is in fact over 7 times higher than the deaths in the US from flu in the under-65 range. This illustrates how bad visualisations are not only easy to misread, but can be actively misrepresentative.