A good data analysis lesson here: Make sure to use multiple Y axes if you are compared line graphs like this.
It is much easier to see the differences at the top of the scale than at the bottom of the scale, but that doesn't mean the shapes of the lines aren't similar if scaled properly. In fact somebody in the comments has made a version with the Y axes normalized, and the shape of the graphs are all pretty much the same, completely contradicting the conclusion the author makes (or if not, the author didn't provide enough clarity on the point he was trying to make).
Classic example of "not challenging your own data" [1]. A tough skill to learn when doing data analysis, because it isn't fun spending a lot of time and effort to try to prove yourself wrong.
It is much easier to see the differences at the top of the scale than at the bottom of the scale, but that doesn't mean the shapes of the lines aren't similar if scaled properly. In fact somebody in the comments has made a version with the Y axes normalized, and the shape of the graphs are all pretty much the same, completely contradicting the conclusion the author makes (or if not, the author didn't provide enough clarity on the point he was trying to make).
Classic example of "not challenging your own data" [1]. A tough skill to learn when doing data analysis, because it isn't fun spending a lot of time and effort to try to prove yourself wrong.
1: http://danbirken.com/statistics/2013/11/19/ways-to-make-fake...