Wednesday, September 5, 2012

Statistics? Experimentation? What the...?

Ciao! Chris here, back with my weekly Neuro blog #THECORTEX, and this time, I want to rant a bit on the complexities of understanding statistical reports and experimentation in scientific papers. Like many people who find themselves plunging head first into piles of assigned articles, I have difficulty getting past the Oxford Dictionary-esque language that researchers love to use. Usually, this isn’t much of an issue (I’m used to it from Shakespeare) but the problem lies in the fact that they use complex vocabulary along with very specialized terms and acronyms that only people highly immersed in the field will understand. It frustrates me to no end, but hey, that’s the status quo, science is professional.

            Moving beyond the wording of papers, I find statistical reporting plain old confusing. I have a general understanding of p-values, error bars, normal distributions, significance of results, the whole 9-yards, but sometimes they use tests that I just have never seen before. I get so lost up in the explanation that I tend to lose track of what the paper is trying to say. When closely analyzed, the statistics isn’t that bad, but the inclusion of their statistical procedure has a tendency to make things clustered for me.
            Lastly, the most confusing thing about experimentation in scientific papers is the different types of procedures used and the figures that special computer programs spit out. I’m extremely familiar with EEG tests from my own research, however experimenters use tests I have never heard of or am not too familiar with, I tend to spend so much time trying to figure out what’s going on.
            It’s crazy how on can spend a few hours trying to understand 5 pages fully, I definitely need more practice!

 What do you think? Drop me a line!

Some Disney Stats 

2 comments:

  1. I think you're right about the explanations of statistical results. I sometimes get very caught up in explanations, and find myself going back to the figure to stare at it again as I wade through the explanation. Sometimes, I even make a list at the outset of the statistical tools they use, and my own personal take on the figures and data before I start reading so I have some sort of anchor so I don't get too lost.

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  2. Let me begin by saying how awesome that picture is, would it be safe to assume you are quite the Disney fan? I completely sympathize with your frustrations, particularly the researchers' use of language; I'm simply not informed enough about their research question to understand the terminology. I feel like it takes for me to get through a paper because I have to re-read each sentence at least twice because I have to try to reason out each word and figure out how it all fits together. I similarly wrote about how confusing the tests researchers use are, because more often than not, they do not explain the method before barreling on into the next point they have to make. It's vexing, but I agree, I definitely need more practice!

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