I have read a lot of studies using an interrupted time series design, e.g., studies using the ‘unexpected event during survey design‘. I have noticed that the better studies using an interrupted time series design all provide great visual presentations of the results. There are relatively easy ways to improve the visual presentation of findings […]
Tag: data visualisation
How to improve your figures #8: Make probabilities tangible
Statistics is about learning from data in the context of uncertainty. Often we communicate uncertainty in the form of probabilities. How should we best communicate such probabilities in our figures? The key point in this post is that we should not only present probabilities in the form of probabilities and the like. Instead, we need […]
How to improve your figures #7: Don’t use a third dimension
Most static figures show information in two dimensions (with a horisontal dimension and a vertical dimension). This works really well on the screen as well as on paper. However, once in a while you also see figures presenting figures with a third dimension (3D). It is not necessarily a problem adding a third dimension if […]
How to improve your figures #6: Don’t use bar graphs to mislead
In a previous post, I argued that the y-axis can be misleading under certain conditions. One of these conditions is when using a bar graph with a non-zero starting point. In this post I will show that bar graphs can be misleading even when the y-axis is not misleading. In brief, bar graphs do not […]
Visualizing climate change with stripes
Climate change is abstract. We do not personally experience climate change in our day-to-day activities (although cimate change is detectable from any single day of weather at global scale, cf. Sippel 2020), and if we are to understand climate change, data – and in particular data visualisation – is crucial. I have recently been reading […]