Today in class we discussed graphs in statistics. The takeaway (for me) was that all graphs are comparisons, which I found was very insightful. When I see graphs in the research papers, I read the caption, legends, look at the graph, go back to the article, until I finally understand what the point of the graph is. This approach that every graph is a comparison seems like a very useful tool to expedite this process. Now I can first identify the two (or more) things that the graph is trying to compare, and the content of that comparison would be the message, or the point, of the graph. I actually used this approach in a meeting today when a post-doc candidate presented her work on audiovisual research. As in other neuroscience research, the graphs contained a lot of colors representing different cortices in the brain and their interactions within. Usually, I would get overwhelmed by the content and the speed of the presentations, but today, I focused on comprehending the graphs as a comparison between two things: hard drop v.s. soft drop, spike v.s. no spike, etc. I'm glad what I learned in class today turned out to be actually practical!