Courses for AMS Majors

The B.S. in Applied Mathematics and Statistics is a joint major that provides the rigor of a BS degree emphasizing topics in applied mathematics and in statistics. Suitable for students interested in employment in many data/quantitatively-oriented fields, or pursuing graduate studies in applied math, quantitative social sciences, natural sciences, or engineering. A combination of 20 courses, totaling 54-59 credit hours, is required to complete the major. Majors will take the requisite QTM coursework, ten required Math/CS courses, and three Math/CS electives.

Please note, students must meet the minimum GPA requirement of 2.0 to graduate with any major or minor from the department.

All classes counting toward the degree must be taken for a letter grade.

 

 

Click here to view Core QTM Coursework

MATH 112: Calculus II

Techniques of integration, exponential and logarithm functions, sequences and series, polar coordinates.

Prerequisites: MATH 111

Credits: 3

MATH 211: Multivariable Calculus

Vectors; multivariable functions; partial derivatives; multiple integrals; vector and scalar fields; Green's and Stokes' theorems; divergence theorem.

Prerequisites: MATH 112 or 112Z

Credits: 3

MATH 212: Differential Equations

This is a standard first semester Differential Equations course which covers first and second-order differential equations and systems of differential equations, with an emphasis placed on developing techniques for solving differential equations.

Prerequisites: MATH 112 or 112Z

Credits: 3

 

MATH 221: Linear Algebra OR MATH 321: Abstract Vector Spaces

MATH 221: Systems of linear equations, matrices, determinants, linear transformations, eigenvalues and eigenvectors, least squares.

Prerequisites: MATH 112 or 112Z

Credits: 4

MATH 321: Axiomatic treatment of vector spaces, inner product spaces, minimal polynomials, Cayley Hamilton theorem, Jordan form, and bilinear forms.

Prerequisites: MATH 250 or 276

Credits: 3

MATH 250: Foundations of Mathematics

An introduction to theoretical mathematics. Logic and proofs, operations on sets, induction, relations, functions.

Prerequisites: MATH 112 or 112Z

Credits: 3

MATH 315: Numerical Analysis

Solution of linear and nonlinear systems of equations, interpolation, least-squares approximation, numerical integration, and differentiation.

Prerequisites: Math 221 or 275 or 321, and CS 170

Credits: 3

MATH 361: Probability and Statistics I

Finite and continuous probability theory, distribution models (binomial, geometric, uniform, normal, Poisson, and exponential), the Chebyshev inequality, expectation and variance, moment generating functions, the central limit theorem, and applications.

Prerequisites: Math 211 or 276

Credits: 3

MATH 362: Probability and Statistics II

Fundamentals of Statistical Inference: estimation, properties of estimators, methods for comparing estimators, confidence intervals, hypothesis testing, regression, and analysis of variance.

Prerequisites: MATH 361

Credits: 3

CS 170: Intro to Computer Science I

Intro to computer science for students who plan serious use of the computer in course work or research. Topics include: fundamental computing concepts, the Linux OS, the X-window system, and the Java programming language. Emphasis on algorithm development with examples highlighting data structures.

Prerequisites: None

Credits: 4

Math/CS Electives

2 Math courses chosen from the following:                       
Math 330 Intro to Combinatorics 3
Math 345 Math Modeling 3
Math 347 Intro to Nonlinear Optimization 3
Math 346 Intro to Optimization Theory 3
Math 351 Partial Differential Equations 3
Math 352 PDEs in Action 3
Math 411 Real Analysis I 3
Math 412 Real Analysis II 3
1 additional course chosen from the following:
Class Number Class Name Credit Hours
CS 171 Intro to Computer Science II 3

Additional CS course at the 200-level or above*

3

Additional MATH course at the 300-level or above*

3

*Cannot include courses already fulfilled in a previous category