Summer 2018
# What is ARIA?
The Arts Research Internship Award supports Undergraduate students pursuing research studies. I worked in the McGill Neurophilosophy Lab under supervision of Dr. Ian Gold and Dr. Gunnar Schmidtmann during the summer of 2018.
You can find the published study at this link and my final report here.
# The Story
During this time I was responsible for facilitating participant studies, but I soon realized that we couldn’t interpret the data I was collecting in the absence of a data analyst. At this point I’d learned enough Python to get through a Software Systems course, so I figured, “Why not try it myself?”.
Below you’ll find the poster I designed with (a small fraction of) my findings from the summer, presented at the ARIA Showcase in 2019.
My partner, Joshua Loong, and I had fun coming up with dozens of different graphs that progressively grew in ambition as we explored heat matrices, moved into 3D spaces, and I finally had the chance to learn what those P values are all about. In the process, I learned how to use Jupyter Notebooks and a few Python libraries including Pandas, Matplotlib, Seaborn, and NumPy. When the new semester rolled around I enrolled in a Stats course knowing I hadn’t even gotten my toes wet when it came to Data Science.
Together we presented our findings to the lab which allowed us to offer recommendations for moving forward; what are some possible theories accounting for the discrepancies in the two datasets we were comparing? Which variable correlations accounted for statistically significant results? Which areas suggested there was more to explore?
This graph above is an early version of the terms matrix featured in the paper.
I’ve shared this story here because it really was the first time I applied my experience in learning how to learn programming skills, to find practical solutions for real problems I was facing.
Design for me, as I’ve mentioned in other posts, is primarily about people, and the interactions that happen between them. Encompassed within this value is the idea that design is a tool for communicating ideas and information, from which data analysis is not exempt.