Last time something from judg.me was posted, there was a lot of criticism about your statistical methods of analysis. You've clearly put a lot of effort into attempting to do a better analysis of the data, and this time there's certainly an improvement in terms of actual analytical methods used.
However, the graphs (as others have said) are terrible. Simply having a graph type available to you doesn't mean you have to use it! For the sake of your readers, please, please, only use one type of graph. Stick with a plain bar chart. Nobody minds that it's not as fancy looking as a pseudo-3D bar chart or one with pointed cones. People want to see the data, not the fancy chart.
An additional point to this is labelling your axes. Please do it! If I can't see clearly what an axis represents, I'm inclined to ignore your data. Regardless of how interesting your data is, I'm going to stop reading if it's presented terribly.
These are the sorts of things that get hammered into you in scientific subjects at school/college. You don't need to do that type of class to know them though. There's plenty of information online about this stuff.[1] Worth noting is section 2.6, "Do not misuse the tools". Bad graphs are to statistics what the <blink> tag is to HTML.
Comments
Last time something from judg.me was posted, there was a lot of criticism about your statistical methods of analysis. You've clearly put a lot of effort into attempting to do a better analysis of the data, and this time there's certainly an improvement in terms of actual analytical methods used.
However, the graphs (as others have said) are terrible. Simply having a graph type available to you doesn't mean you have to use it! For the sake of your readers, please, please, only use one type of graph. Stick with a plain bar chart. Nobody minds that it's not as fancy looking as a pseudo-3D bar chart or one with pointed cones. People want to see the data, not the fancy chart.
An additional point to this is labelling your axes. Please do it! If I can't see clearly what an axis represents, I'm inclined to ignore your data. Regardless of how interesting your data is, I'm going to stop reading if it's presented terribly.
These are the sorts of things that get hammered into you in scientific subjects at school/college. You don't need to do that type of class to know them though. There's plenty of information online about this stuff.[1] Worth noting is section 2.6, "Do not misuse the tools". Bad graphs are to statistics what the <blink> tag is to HTML.
[1, The UNs guide to presenting statistics]: http://www.unece.org/fileadmin/DAM/stats/documents/writing/M...
Agreed - and I've updated the graphs. Thanks for the comments!