Mathematics Minor

The mathematics minor requires a minimum of 18 credit hours.

All prerequisites must be completed prior to enrollment in the following courses.
A grade of C- or higher must be achieved in the 200-level courses listed below.

MATH 231: Calculus I
4 credit hours

 It is strongly recommended that students have completed two years of high school algebra and one semester of high school trigonometry in order to be successful in this course. A study of the fundamental principles of analytic geometry and calculus with an emphasis on differentiation.

MATH 232: Calculus II
4 credit hours

Prerequisite:  MATH 231 or MATH 236. It is recommended that students receive a grade of C or better in MATH 231 or MATH 236 to be successful in this course. Continuation of Calculus I including techniques of integration and infinite series.

MATH 233: Calculus III
4 credit hours

Prerequisite:  MATH 232. It is recommended that students receive a grade of C or better in MATH 231 to be successful in this course. 
Functions of two variables, partial differentiation, applications of multiple integrals to areas and volumes, line and surface integrals, and vectors.

MATH 235: Linear Algebra
3 credit hours

Prerequisite:  MATH 232.  Study of linear transformations, matrices and vector spaces.

Choose one course from the following (3 hrs.): 

CSCI 340: Numerical Analysis
3 credit hours

Prerequisite:  MATH 231 or MATH 236, and MATH 232. 
Numerical solutions to mathematical problems are studied. Topics include approximating solutions to equations, interpolation, numerical differentiation and integrating, and numerical linear algebra.

MATH 261: Introductions to Data Science
3 credit hours

Prerequisites: MATH 227 and CSCI 152. An introductory exploration of the data science process, its uses, and its applications. Students will focus on the derivation of actionable knowledge from data using the data science pipeline. Pipeline topics include data acquisition, cleaning of data, transformation of data, analysis of data, and interpretation of data. Analysis of data includes an introduction to both statistical and machine learning techniques. Interpretation of data will include an introduction to data visualization. Additionally, the course will address the role of data science and the implications of its use in our culture, our world, and our individual lives. The course uses a problem-based approach where students will engage with other students and with the course materials.

MATH 301: Abstract Algebra
3 credit hours

Prerequisite:  MATH 234 or CSCI 241 and CSCI 262MATH 235. 
The elementary properties of groups, rings and fields are developed.

MATH 326: Probability Theory
3 credit hours

Prerequisite: MATH 232. It is recommended that students receive a grade of C or better in MATH 232 to be successful in this course.
This course includes an introduction to probability theory, discrete and continuous random variables, mathematical expectation and multivariate distributions.

MATH 327: Mathematical Statistics
3 credit hours

Prerequisite:  MATH 326. It is recommended that students receive a grade of C or better in MATH 326 to be successful in this course. 
This course takes the material from MATH 326 into the applications side of statistics including functions of random variables, sampling distributions, estimations and hypothesis testing.

MATH 330: Geometry
3 credit hours

Prerequisite:  MATH 234. Foundations of Euclidian geometry from the axioms of Hilbert and an introduction to non-Euclidian geometry.

MATH 366: Differential Equations
3 credit hours

Prerequisite:  MATH 232A first course in ordinary differential equations.

MATH 421: Real Variables
3 credit hours

Prerequisite:  MATH 233MATH 234. It is recommended that students have completed MATH 301 in order to be successful in this course. Real number system, set theory, continuity and differentiability.

MATH 428: Regression Analysis
3 credit hours

Prerequisite: MATH 227 or MATH 327. In almost any study, there is the task of predicting or explaining the behavior of a particular variable. In most cases such research is possible through the analysis of a relationship of this variable with some others. Such interactions are not pre-determined and are of a random nature. A mathematical model of such relationship becomes one of the most important tools of study. Construction, examination and use of such a model are subjects of the regression analysis.

MATH 432: Complex Variables
3 credit hours

Prerequisite:  MATH 233MATH 234. A study of complex numbers, analytic functions, complex integration, residues and series.

MATH 440: Topology
3 credit hours

Prerequisite:  MATH 234. An introduction to point-set topology. Metric spaces, connectedness, completeness and compactness are some of the topics discussed.

MATH 290, 390, 490: Selected Topics
1-3 credit hours

Selected Topics are courses of an experimental nature that provide students a wide variety of study opportunities and experiences. Selected Topics offer both the department and the students the opportunity to explore areas of special interest in a structured classroom setting. Selected Topics courses (course numbers 290, 390, 490) will have variable titles and vary in credit from 1-3 semester hours. Selected Topic courses may not be taken as a Directed Study offering.


MATH 234: Introduction to Mathematical Proof
3 credit hours

Prerequisite:  MATH 231 or MATH 236. It is strongly recommended that students have completed MATH 232 to be successful in this course. A careful introduction to the process of constructing mathematical arguments, covering the basic ideas of logic, sets, functions and relations. A substantial amount of time will be devoted to looking at important forms of mathematical argument such as direct proof, proof by contradiction, proof by contrapositive and proof by cases. Applications from set theory, abstract algebra or analysis may be covered at the discretion of the instructor.