Math, Data & Computing
Data analysis serves as a vital means of making sense of the complex realities in our world today. Carrying out observations across individuals and/or time allow us as designers to identify patterns that may emerge, and is something that I have experience with through various courses. Collecting, cleaning, processing and validating quantitative data is a big part of MDC that I have also spent time developing.
I have also worked on creating visual representations of data through code for both analysis and presentation, using tools such as Jupyter and Processing. Identifying this expertise area as an opportunity of growth early on in the semester allowed me to spend a good amount of time working on a personal project that eventually turned into an integrated component of the demoday setup.
Inferential statistical analysis and Cohen’s d are two specific examples of quantitative analysis methodologies that I have applied in projects and learned to use. Alongside this I also learned briefly about practical applications mathematical concepts such as Catmull-Rom spline curves.
