# MTH - Mathematics Major

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### Program Title

### Program Type

### Degree Designation

### Department(s)

### 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.

### Requisites

# Requirements for the Major (48 credits)

### I. Core (36 credits)

Complete all of the following:

course - Calculus and Analytic Geometry I

course - Topics in Single and Multivariable Calculus__OR__course - Calculus and Analytic Geometry II

course - Calculus and Analytic Geometry III

course - Introduction to Statistics

course - Introduction to Computer Science in Python

course Object Oriented Programming in Java,__OR__course Introduction to Computer Science in JavaScript__OR__course Statistical Computing in R__OR__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

### Notes

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.