Section author: Danielle J. Navarro and David R. Foxcroft

Summary

Perhaps I’m a simple minded person, but I love pictures. Every time I write a new scientific paper one of the first things I do is sit down and think about what the pictures will be. In my head an article is really just a sequence of pictures linked together by a story. All the rest of it is just window dressing. What I’m really trying to say here is that the human visual system is a very powerful data analysis tool. Give it the right kind of information and it will supply a human reader with a massive amount of knowledge very quickly. Not for nothing do we have the saying “a picture is worth a thousand words”. With that in mind, I think that this is one of the most important chapters in the book. The topics covered were:

• Common plots. Much of the chapter was focused on standard graphs that statisticians like to produce: histograms, box plots and bar graphs.
• Saving image files. Importantly, we also covered how to export your pictures.

One final thing to point out. Whilst jamovi produces some really neat default graphics, editing the plots is currently not possible. For more advanced graphics and plotting capability the packages available in R are much more powerful. One of the most popular graphics systems is provided by the ggplot2 R package, which is loosely based on “The grammar of graphics” (Wilkinson, 2006). It’s not for novices. You need to have a pretty good grasp of R before you can start using it, and even then it takes a while to really get the hang of it. But when you’re ready it’s worth taking the time to teach yourself, because it’s a much more powerful and cleaner system.