student's t-distribution

The student’s t-distribution (now more commonly known as just the t-distribution) was proposed by William Sealy Gosset who published his work under an anonymous pseudonym, “Student,” thus garnering the name student’s t-distribution. Being a student was my main intention when I entered UW, and as a student, I have had the chance to take some incredible classes.

data visualization

CSE 412, data visualization, is a class that has had a lasting impact on my way of thinking to this day. Prior to the class, I had always considered math, and therefore statistics, to be inherently uncreative fields. It’s just numbers and calculations that produce one final answer. However, this class forced me to think about the role of design in effective data visualization, including factors like color, shape, and motion. Suddenly, statistics became intertwined with art and creativity, which I felt unprepared to embrace initially. I was worried that since I hadn’t exercised the artistic side of my brain in so long, I would be “bad” at data visualization. The projects in this class really challenged me to venture out of my comfort zone and experiment with my creativity and imagination. I ended up designing a data visualization that looked like a city skyline that responded to live sound input from my computer microphone, one that was (purposefully) misleading, and a whole series focused on car accidents. I now really enjoy considering the creative aspects of data visualization and understand how failing to be intentional with design could result in deception or miscommunication. Data visualization is the beautiful intersection between art and statistics, and while the creative freedom was something I dreaded at first, I have since come to only value it. This takeaway has extended beyond just visualization, as I’ve realized creativity is interlaced with all aspects of statistics from experimental design to selecting variables and choosing which models to use. Statistics is all about storytelling.

covid vaccine trials

For my final project in the STAT 34X series, we were given the task to analyze data from a COVID vaccine trial. For the first time in this class, we were allowed to use any type of analyses or statistical tools from the entire year, which gave us a lot of freedom, but also a lot of places to possibly mess up. Our final paper involved proofs, graphs, and assumptions that we later learned might not have been the best simplifications. Nonetheless, in the end we did conclude that the vaccine was effective. This project was a great way to finally apply all of the theory that we had been working on for a full year toward a real-world problem. Before completing this project, I didn't realize how much freedom there was in statistics. Statisticians have a huge toolkit of tests and models, and they have to navigate between them to choose the right one, which might not always be straightforward. The more I work on statistics, the better statistical intuition I will hopefully build.

playing games during class??

My favorite HONORS class that I’ve had the opportunity to take has to be HONORS 221: Game Theory. It was the perfect combination of all my favorite subjects: math, statistics, biology, psychology, and GAMES! The class was so collaborative and everything was done in groups, whether that be gambling or spending gollars (game theory dollars) to buy prizes. We played games (simple, but games nonetheless) every class and applied these otherwise simple games to real life scenarios in fields ranging from evolution to sports. For my final paper, my partner and I decided to tie a quarter of game theory concepts into our least favorite company, Nestle, to explain how large corporations exploit innocent consumers by simply knowing how to play these very small games. Understanding these basic games can really go a long way in unpacking phenomena across the world. To this day, I still think about the concepts taught in this class when it comes to making decisions.