Mathematics: Mathematical Modeling

The world around us is filled with important, unanswered questions—mathematical modeling can take us a long way in developing a solution or understanding.

Mathematical models are used in the natural and social sciences—and beyond—to help explain and make predictions about the behavior of the world around us. Being able to define a problem and then formulate, analyze and interpret information using mathematical models will benefit students in whichever path they choose to pursue after graduation. Emmanuel's major in mathematics with a concentration in mathematical modeling is also an excellent complement to many courses of study, as the subject is integral to analyzing real-world scenarios in industries from public health and city planning to economics and criminology.

View the 2018-2019 Academic Catalog to find course titles, numbers and descriptions.

Requirements for a B.A. in Mathematics with a Concentration in Mathematical Modeling

  • MATH 2101       Linear Algebra
  • MATH 2103       Calculus III
  • MATH 2109       Discrete Methods
  • MATH 2113       Applied Statistics
  • MATH 3101       Real Analysis
  • MATH 3107       Abstract Algebra
  • MATH 4157       Senior Seminar

Three electives from this list:

  • MATH 2107       Differential Equations
  • MATH 2111       Mathematical Modeling in the Sciences
  • MATH 2115       Introduction to Programming with MATLAB
  • MATH 3113       Special Topics in Mathematics (when related to Mathematics Modeling, with department approval)
  • MATH 4194/95  Research Internship I and II (when related to Mathematics Modeling)

In addition to the courses required for a Mathematics Major, students will complete the following learning goals:

  • Understand and connect concepts of mathematics with other disciplines, and formulate and analyze mathematical models appropriate for an intended application.
  • Use technology and software programs (e.g. LaTeX, Excel, R, MATLAB) to analyze mathematical models.  
  • Interpret mathematical solutions in terms of the real world application, and effectively communicate results to others, especially non-mathematicians.

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