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Meet a Member: Jake Tan


Jake Tan is a junior at Wissahickon High School, which is in southeastern Pennsylvania. He is a subsystem leader on his school’s robotics team, captain of the marching band, and JV captain for the lacrosse team. He has done two data science projects and presented them at both the 2022 and 2023 JSM. I also founded a nonprofit organization, called Youth 3D (@youth__3d), that teaches 3D printing to kids in my local community. He received special recognition at the Speed Session for the section at JSM 2023 for his project “Team Contributions to the Alliance in FRC Regional Competitions”.





Why did you decide to go into Statistics/Data Science?


I kind of fell into it. Back in my freshman year in high school, I had found a cool article which described a case study that discussed international conflicts with a certain power dynamic: a rising power and a ruling power, also known as the Thucydides Trap. What the case study did was analyze whether these cases would break out into war or not. The concept was so interesting to me that I wrote three essays about the topic for my gifted language arts class.

However, I wanted to go deeper, and I got help from my dad, a statistician, to teach me R in order to create a model that could predict if a new case would break out into war after x years since the rival dynamic began. This first rudimentary exposure to survival analysis was my gateway into the world of data science. Since I had been dragged to JSM by my parents since elementary school, I wanted to present my findings to someone else other than my language arts and history teachers who I’m sure were tired of hearing about it. At JSM 2022, I got a surprising amount of questions during my poster session, a lot from people who were surprised that I was only 15.


Another exposure I had to statistics was my rookie year on my robotics team. While I was interested in the mechanical subteam, the team makes every member scout and collect data on the performance of individual teams so we can pick a good alliance for playoffs. In my freshman year, I spent three of our four competitions at least partially on data entry and data collection for all four competitions. Since Wi-Fi is disabled near the playing field to prevent connection disruptions with the robots, I often found myself tucked in a cafeteria or hallway where I could manually input illegible data written on paper sheets that would be run to me at the end of every match.


With so much downtime in between scouting sheet runs, I found myself exploring the various graphs and direct analyses that had been whipped up by the team’s Google Sheets guru. This pushed me to start attending scouting meetings and become more active in the game strategy process which led me down the path of sports statistics, which was the topic of my speed session presentation at JSM 2023.


What's a class/workshop at your workplace/university that you wish you could take and why?


I wish I had time and course space to take the AP Statistics during my high school career. But with so many competing courses, it doesn’t look like I can fit it in. When I went to the Wharton Data Science camp this summer, many of my friends at the program were constantly comparing the camp to AP Stat. While I’m fairly certain that I have likely inadvertently learned most of the content of the class, I would really like to take the course.


What Statistics topic do you think is the most difficult to learn well?


I’ve only learned some basic statistics topics. I learned a bit about neural networks at the Wharton Data Science camp this summer. While I find it interesting, I found I really only understand them at a surface level and would love to have more time to take a deeper dive with them to be able to actually apply what I have learned to a real-world problem.


What advice would you give to someone who is new to teaching statistics?


While this is more general advice to new teachers, I think it is extremely important to be constantly conscious of the knowledge level of your students. Being able to definitively decide how much background information you will need to complete your lesson is integral to being both efficient and effective as a teacher. I have learned through personal experience that laying a solid foundation is much more impactful than backtracking to teach basic concepts the teacher falsely assumed the students already understood.


What is your go-to source for data?


In general, I use Kaggle whenever I need a dataset for a school or passion project. Because of my robotics team, I sometimes find myself browsing The Blue Alliance website, which has the complete FIRST robotics competition data since the inception of the program, as it has a treasure trove of interesting team dynamics which can be seen without even watching a single match from a specific competition.


What do you enjoy doing when you’re not working?


I love spending time with friends. Whether at robotics, marching band, lacrosse practice, or playing games online, you can always find me having a great time with my friends. When I’m not with my friends, I enjoy listening to music and CAD(Computer Aided Design)ing things to 3d print.


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