Introduction
Do you know the popular phrase: “There are three kinds of lies: lies, damned lies and statistics”? It illustrates the common distrust of numerical data and the way it’s displayed. And it has some truth: for too long, graphical displays of numerical data have been used to manipulate people’s understanding of ‘facts’. There is a basic explanation for this. All information is included in raw data – but before raw data is processed, it’s too much for our brains to understand. Any calculation or visualisation – whether that’s as simple as calculating the average or as complex as producing a 3D chart – involves losing a certain amount of data, so that we can take it in. It’s when people lose data that’s really important and then try to make big statements about the whole data set that most mistakes get made. Often what they say is ‘true’, but it doesn’t give the full story’
In this tutorial we will talk about common misconceptions and pitfalls when people start analysing and visualising. Only if you know the common errors can you avoid making them in your own work and falling for them when they are mistakenly cited in the work of others.
