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MATH 340 Mathematical Modeling

Mathematical modeling is the investigation of real world phenomena using mathematical tools. This course includes topics such as dynamic and stochastic modeling (differential equations and discrete-time equations), as well as optimization modeling. Applications will include problems from such areas as the physical and biological sciences, business, and industry.

Special information

Prerequisites: For Applied Mathematics Majors: MATH 320 Probability AND MATH 315 Linear Algebra and Applications. Prerequisites: For Mathematics Teaching Majors: MATH 215 Discrete Mathematics, MATH 315 Linear Algebra and Applications, and STAT 201 Statistics I. Students whose prerequisites are not identified by the system should contact the Math and Statistics Department for an override at
4 Undergraduate credits

Effective August 1, 1998 to present

Meets graduation requirements for

Learning outcomes


  • Investigate the literature and learn new methods for modeling and solving real-world problems.
  • Recognize and utilize appropriate deterministic and/or stochastic mathematical models to abstractly represent and solve real-world problems with discrete and continuous dynamical systems.
  • Synthesize the knowledge and skills obtained in the mathematics major curriculum to solve problems in new contexts.
  • Write technical reports and give presentations on mathematical modeling.