LENGTH VS HEIGHT
So! Here we go, ready for the first post.
I will focus on the simplest of the graphs - bar graph.
It is actually the most powerful type of graph as human eye is very good at comparing heights and can easily decipher the information from it. Additionally, it is the most commonly used type of graph, so people are used to reading it.
So... can it actually be improved? It mostly does its job anyway, right?
Well, for some of the cases it is better to use the length to encode the values rather than height. It is most useful when the labels are quite long. For example (He et al. 2016):
when rearranged the graph looks like this:
As you can see the labels are much easier to read (no head twisting!) and at the same time the differences between conditions remian easily readable.
Other authors chose to move the labels to the side in the form of a classic legend (Lin-Hendel et al. 2016):
However, with that many shades of grey it is a bit hard to get all the information at once and you have to move back and forth between the legend and the graph.
In the revised version, it is much clearer to read which condition belongs to which bar:
And finally, when there are many bars in one graph it might help to add a light grey bar to highlight the similar group of conditions, like in the following example (Auer et al. 2016):
As you probably noticed I didn't only rotate the graphs 90 degrees, but changed the shading, removed some non-data ink and changed other details. I will try to cover them in the upcoming posts, so stay tuned! Also, if you have any comments - please share.