A capstone course intended to culminate the core mathematics major studies and should be taken at or near the end of the program. Discusses principles and methods of constructing, analyzing, interpreting, evaluating, and refining mathematical models. Compares analytic and simulation, discrete and continuous, deterministic and stochastic models.
- Make a difference between mathematical systems and mathematical models. Understand will that there are no general recipes for direct applications to different classes of modeling problems, that the overwhelming complexity of a real life situation does not lend itself to immediate success in a do-it-yourself environment.
- Compare and classify models as deterministic, probabilistic, linear, nonlinear.
- Discuss how the model can be tested against real-world data. Indicate how models can be refined and improved.
- Know how to do library and other research to pursue investigation of a chosen model.
- Understand how numerical methods work to solve problems of mathematical modeling in realistic setting.
- Select and apply effectively appropriate algorithms based on ready-to-us programs to obtain numerical and/or graphical representation of the constructed model.
- Interpret correctly computer output. Present clear and convincing description with sufficient logical justification of the modeling results.
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College of Letters and Sciences
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