I started the morning by finishing up the graphing features of the multi data analyzer so that it had graphing by range functionality. I then went back through and adjusted how we took the averages and combined data, so that it would be easy to instead take medians. I looked up what the median equivalent of standard deviation was and found out that it was median absolute deviation (or MAD). I implemented this metric, and then made some graphs of medians with MAD error bars instead of averages with standard deviation error bars. It still wasn’t perfect, but it looked better, and one plot in particular looked excellent. I then started commenting through EVERYTHING so that any future researcher will know how the data tools worked. Luckily, because I had already completely changed it to an OO approach the commenting was not that bad as I didn’t have to explain any magic numbers. Vidushi then asked me to work on making the graphs more readable for the poster so I did that for 30 minutes, and gave her our two best graphs which looked pretty good and bold. The poster is looking excellent, as a side note. With just two days left my remaining jobs are: 1. Comment the swift code which I never commented, 2. Publish my python code and swift code to our repository for posterity’s sake, 3. Write the data analysis sections of the poster and paper.