Both senior seminar and senior thesis satisfy the Bates W3 writing requirement and highlight mathematical research, presentation, writing, and group collaboration. Senior seminar is a good choice for students wanting to improve all these, with special emphasis on presentation and group collaboration. Senior seminars also involve writing, as well as mathematical research on topics curated by the instructor.

For the 2025-2026 academic year, the senior seminar topic is Spatial Statistics and Spatial Data Science, taught by Professor Laurie Baker.

To ensure the senior seminar is an enriching experience, the math department keeps class sizes relatively small and even. To help the department place students into senior seminars, each junior math major who would like to take a senior seminar completes a request form by NOON on the last day of Winter Semester classes of the junior year, that is, by 12:00pm (noon) on Friday, April 11, 2025. Some details:

• The request form seeks background information on the student, the student’s preferences regarding senior seminar, and the student’s reasoning behind their preferences.
• It is a good idea for juniors to discuss the choice between senior seminar and senior thesis with faculty members before completing the request form.
• The department meets to consider all senior seminar and thesis proposals. The department chair typically notifies students of the results of the meeting during Short Term.
• The course description for the Winter 2026 senior seminar is below.

MATH 495?: Spatial Statistics and Spatial Data Science

Everything happens somewhere. Spatial statistics is a branch of statistics that focuses on analyzing data with a geographic component, providing essential tools for understanding patterns, dependencies, and processes in space. From modeling disease outbreaks and crime hotspots to estimating air pollution levels at unmeasured locations, spatial statistical methods help answer key scientific and policy-driven questions.

In this seminar, we will explore fundamental spatial statistical concepts, including point processes (e.g., modeling earthquake occurrences or crime hotspots), random fields (e.g., predicting soil contamination levels or temperature variations), and spatial interpolation (e.g., estimating air pollution levels at unmeasured locations). We will emphasize both the mathematical foundations and practical applications of these methods, using real-world datasets to develop proficiency in spatial analysis.

A key component of this seminar is student leadership in learning. Students will be responsible for leading class discussions, presenting on assigned topics, and guiding peers through critical concepts in spatial analysis. Writing assignments will also incorporate technical documentation using Quarto, Markdown, and LaTeX to develop professional documentation and reproducible research workflows. Through hands-on group projects analyzing real data and writing-intensive assignments, students will develop expertise in accessing and analyzing spatial data, interpreting results, and effectively communicating insights. Coding experience is recommended but not required. There are no prerequisites for the seminar and students who have not taken Math 214 and Math 215 are very welcome.

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