Dartmouth College

What you'll study

The programme blends core courses in pure mathematics with applied and statistical coursework, allowing students to tailor study toward theory, computation or data science. Typical first‑year and early courses include multivariable calculus, linear algebra, and introductory probability and statistics. As you progress you will encounter real analysis, abstract algebra, differential equations, and courses in mathematical modelling.

On the statistics side, students take probability theory, mathematical statistics, regression and experimental design, and computational statistics. Electives commonly cover numerical analysis, optimisation, stochastic processes, time series, machine learning, and high‑dimensional statistics. There are opportunities to take cross‑listed courses with computer science, economics, engineering and the life sciences for applied contexts.

A key feature of the undergraduate experience is independent work: many students complete an advanced seminar or a senior thesis/research project under faculty supervision. Seminars and small honours classes emphasise proofs, problem solving and presentation of results. Lab‑style and computing components introduce practical data handling, simulation and reproducible analysis using common scientific tools and programming languages.

Entry requirements

Admission to Dartmouth College is competitive and assessed holistically. Successful applicants typically present a strong high‑school record with a focus on mathematics: calculus (or equivalent) and advanced courses where available. Admissions committees look for evidence of quantitative aptitude demonstrated through coursework, teacher recommendations, and academic projects or competitions.

Preparation in related areas such as physics, computer science or advanced placement in mathematics strengthens an application. Prospective transfer students should show college‑level mathematics preparation and a record of sustained academic performance. Applicants are also evaluated on written materials, extracurricular engagement and intellectual curiosity; interviews and additional materials may be part of the process.

Career prospects

Graduates with a mathematics and statistics degree from Dartmouth are well placed for a wide range of careers. Common pathways include data science, quantitative roles in finance and consulting, actuarial work, software engineering, and analytics positions across industry. The programme also provides strong preparation for graduate study in mathematics, statistics, computer science, economics and related fields.

Alumni work in academia, research institutions, government agencies, technology firms and start‑ups. The combination of theoretical rigour and applied statistical training equips students for roles that require critical thinking, quantitative modelling and data‑driven decision making. Many students further develop practical skills through internships, research assistantships and cross‑disciplinary projects that help transition into professional roles.

Why study at Dartmouth College

Dartmouth offers an undergraduate‑centred environment with small class sizes, close faculty mentoring, and ready access to research opportunities. The Department of Mathematics and Statistics emphasises personalised advising and supports students undertaking independent research or senior theses with faculty across pure and applied areas.

Students benefit from interdisciplinary connections across the liberal arts campus as well as professional schools, enabling combined coursework with computer science, economics, the Thayer School of Engineering and business electives. The College's emphasis on undergraduate teaching means students can expect early exposure to advanced topics, plentiful seminar offerings and a collaborative academic community.

Outside the classroom, students can augment their studies through internships, summer research, study away options and student organisations focused on mathematics, statistics and data science—providing both practical experience and professional networking opportunities.