Statistics, Data Science & Design Projects
Here is a collection of statistical projects I worked on during my time at UC Santa Barbara. These projects served as a platform for me to apply my expertise in various tools and programming languages, including R, tidymodels, and Python's pandas library.
Taking in a dataset of one of the greatest shooting guards and 3-point shooters of all time, Klay Thompson, I split, trained, and tested data to create an optimal machine learning model that predicts Klay's points scored and other statistics.
I created a video for my Real Analysis class exploring how we can use math and physics to achieve the optimal release angle and velocity of a basketball free throw.
I analyzed data from the 2016 and 2020 elections through paired t-tests, Wilcoxon signed-rank tests and other R data science tools. I focused on key swing states and investigated the narrowness of margins, as well as how the accuracy of polling can be improved.
In my Survival Analysis class, a group of friends and I studied competing risks models, which differ from standard survival models given that there are more than two outcomes for each observation. This project analyzed cardiovascular data.
