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MTH - Mathematics Major

Program Title


Program Type


Degree Designation


Program Description

Major effective prior to 2011.

Modifications Made to Curriculum: Fall 2020

Mathematics lies at the heart of the liberal arts. Based in abstraction and logical reasoning, mathematics is both a body of knowledge and an elegant and useful way of perceiving our world. Through mathematics, we can distill and describe the otherwise hidden patterns and relations among things. Because of this, mathematics finds ubiquitous application, from the natural and social sciences to the humanities and the arts. Precise abstraction and quantification play an increasingly important role in these diverse areas, and the study of mathematics can provide a foundation for any of them.

Free Form Requisites

Requirements for the Major (48 credits)

I. Core (36 credits)

Complete all of the following:

  • course - Calculus and Analytic Geometry I OR course - Topics in Single and Multivariable Calculus

  • course - Calculus and Analytic Geometry II

  • course - Calculus and Analytic Geometry III

  • course - Introduction to Statistics

  • course - Introduction to Computer Science in Python OR course Object Oriented Programming in Java, OR course Introduction to Computer Science in JavaScript OR course Statistical Computing in R

  • course - Discrete Mathematics

  • course - Linear Algebra

  • course - Foundations of Higher Mathematics

  • course - Probability

II. Proof-Based (4 credits)

Complete 4 credits, selected from the following:

III. Electives: Two electives from the following, with at least one at the upper-level (8 credits)

Complete 8 credits, at least 4 of which are upper level.

  • course - Introduction to Logic

  • course - Differential Equations

  • course - Mathematical Physics

  • course - Real Analysis (if not taken as the proof-based course)

  • course - Abstract Algebra (if not taken as the proof-based course)

  • course - Special Topics in Mathematics

  • course – Stochastic Processes

  • course – Optimization and Machine Learning Mathematics

  • course – Advanced Linear Algebra

  • course – Complex Variables

  • course - Modeling and Simulation

  • course - Symbolic Logic

  • course - Applied Regression Analysis

  • course - Statistical Theory (if not taken as the proof-based course)

  • course - Bayesian Statistics

  • course - Statistical Machine Learning

  • course - Computational Modeling of Neural Systems

  • Other DATA and STAT classes at the 200-level with advisor approval and the submission of a Ladder petition


For students also majoring in physics, course, course, course, and eight additional intermediate- or upper-level credits may count for both majors.

Students wishing to pursue graduate study in mathematics are urged to take both course and course.