- Hometown: Ningbo, China
- Program & Year: MS Capstone, second year
- Advisors: Ken Rice, academic advisor; Jon Wakefield and Deborah Donnell, advisors on research work
- “I study biostatistics because I care about the rationale and statistical rigor underlying scientific studies.”
Q&A
What motivated you to pursue an MS in biostatistics, specifically, the MS Capstone program? Were any particular experiences, projects, or moments that influenced your decision?
I studied ecology during my undergraduate, and while reading research papers, I often found it straightforward to understand the research purposes and conclusions. I realized, however, that I didn't know much about the statistical method sections, which felt like an important piece of the puzzle that was missing. This feeling motivated me to pursue an MS in biostatistics in a systematic way as it is an indispensable part of conducting reliable research. I also wanted an opportunity to apply statistical skills to real-world scenarios and see their application beyond the academic world, and the Capstone program is suitable for both purposes.
Why UW Biostatistics and not another university?
UW Biostatistics is a prestigious department with diverse interests and a strong emphasis on rigorous statistical training. Additionally, the small cohort size helps build a closely-knit atmosphere within the department. The course design with a capstone project is unique and appealing. Seattle is also a wonderful place to live.
How would you describe your experience as a UW Biostatistics student? What’s been the most valuable part of the experience?
I've really enjoyed my experience here. The courses are of high quality, students are supportive of one another, and the faculty members I've interacted with are super approachable and helpful. The department provides resources for job hunting, and there are plenty of research opportunities available. It is a great platform. I've worked on projects in collaboration with PhD students and even professors from other departments and universities. The most valuable part for me has been the opportunity to engage with other people in this field. Conversations with fellow students, alumni, and faculty have given me valuable insights into their perspectives, motivations, and suggestions, which have helped me understand more about the field and clarify my future goals.
What advice would you give to a student who is considering the UW Biostatistics MS Capstone program?
If you're considering the UW Biostatistics MS Capstone program, my first piece of advice would be to explore the three pathways offered by the program. Each pathway has specific required courses, so take the time to review these options and assess whether they align with your interests. If there are particular topics you’re passionate about, I recommend exploring the faculty members’ research on the UW website to see if people are working on those topics. Do you want a guaranteed hands-on experience through a capstone project? If so, this program could be a great fit.
If you are still exploring the field and uncertain about your specific focus, you could reach out to current students or alumni. Ask about their experiences in the program, what they valued most, and how it helped shape their careers, and see whether their answers resonate with you.
Anything else you’d like people to know about you, your student experience, the field, etc.?
I am from a non-math/stat undergraduate background, so I initially worried about keeping up with the pace of the courses and whether it might affect my chances of finding research opportunities. However, it didn't because of the well-structured courses and I’ve always felt supported by both faculty and fellow students. To those coming from a similar background, I want to say: don’t be intimidated. Put your heart into it, and know that no matter where you start, it won’t stop you.
Are you interested in earning your Master of Science in Biostatistics? Learn more about the MS Capstone program, including the curriculum, resources available, and examples of student work.
