Minors

Minors in Mathematics

Mathematics Minor

Program Description: Mathematicians study concepts and theories used to solve problems involving quantitative relationships. Opportunities for mathematically-oriented graduates exist in such areas as physics, engineering, space technology, economics, business management, statistics, actuarial sciences, operations research, medical research, environmental sciences, and teaching. The Mathematics minor prepares graduates for positions in industry and teaching or to continue their education in graduate programs.

Contact: Chair, Department of Mathematics

Mathematics Minor

Required Courses

MTH

Course Title

Cr. Hrs.

245

Calculus I

4

246

Calculus II

4

350

Applied Linear Algebra & Differential Equations

3

Three MTH courses numbered >300

7

18 hours

Data Science Minor

Students seeking to earn the Data Science Minor must successfully complete six courses for a total of 18 credit hours. All students will complete two courses forming a "statistics sequence" (MTH 360/361 and MTH 362) and two courses forming a "data science sequence" (MTH 365 and MTH 366). The remaining two courses will be selected from options in mathematics, computing sciences, and other disciplines across the University.

Required Courses

MTH

Course Title

Cr. Hrs.

360
or
361

Elementary Probability and Statistics
 
Probability and Statistics in the Health Sciences

3

362

Statistical Modeling

3

365

Introduction to Data Science

3

366

Machine Learning

3

 

The other two courses in the Data Science Minor will be satisfied by completing a Computing Course and a Discipline Course.

Computing Courses (choose 1 of 3: 3 credit hours)

  • CSC 221: lntro to Programming
  • CSC 321: Data Structures
  • CSC 427: Data Structures and Algorithm Analysis

Discipline Courses (choose 1 of 18: 3 credit hours)

  • ANT/SOC 570: lntroduction to Geographic Information Systems
  • BIA 472:Visual Analytics and Visualization
  • BIA 480: Business Analytics
  • BIA 484: Data MiningTechniques
  • BIA 485: Applications of Artificial lntelligence
  • BIO 501: Bioinformatics
  • CSC 321: Data Structures
  • CSC 327: Data Structures and Algorithm Analysis
  • ECO 418: Econometrics
  • ECO 433: Regional Economic Analysis
  • FIN 505: FinancialModeling
  • HIS 316: lntroduction to Digital Humanities
  • HIS 435: Digital Cultures
  • MKT 343: Marketing Research
  • MKT 479: Marketing Analytics Seminar
  • PHYS 553: Computational Physics
  • PLS 421: Public Opinion, Political Behavior, and Survey Research
  • PSY 370: Applying Research Methods and Statistics in Psychology

 

6

18 hours


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