We started the day today by working on our presentation for tomorrow (after getting back from Discovery Day). I don’t think there was very much to do, since I had pretty much finished up the slides, but the kinds of data analysis being done has changed a lot since I wrote them. Adam changed that, I fixed some small things, and we did a trial run. It came to around 11 minutes, at which point Adam reminded me that we need a results section now that we actually have results! So we added in a slide with the results that we do have — successes such as the few statistically significant differences, actually being able to capture such fine data, and so on. We also added a few reasons that we think explain why our data is not as good as we hoped, which I think paves the way for future work.

After this I spent most of my time doing some statistical analysis. I was pretty confused by how many of our distributions seemed to be normal, so I went through and ran all of them (which definitely took a while), to equally surprising results. Only two of our 36 distributions are apparently not normal. I’m still confused, but I think more and more that these results are just a consequence of the small sample size. Having finished this, I did some research on implemented paired t-tests in SciPy, and found two types: the “related” and the “independent”. Running the paired produced the problem of not having equal sized arrays, which was (as Prof Medero later explained) because the related distributions are supposed to be data sets that can be paired up. The independent test, which I only ran for a couple of pairs, suggests that most of them are not different distributions in a statistically significant manner. However, as Adam changes his analysis, I can always run pairs that look visually to be more useful.

I then did some documentation things — created a GitHub repo, put some initial useful documents in there, and moved all my Google Docs stuff to Evernote. Tomorrow, after the presentation, my intention is to work on the poster and the paper, and run some statistical tests if necessary.

### Like this:

Like Loading...

*Related*