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Detailed Course Information


Fall 2013
Oct 05,2022
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Information Select the desired Level or Schedule Type to find available classes for the course.

The descriptions and topics of this course vary from semester-to-semester, as well as from instructor-to-instructor. Prerequisite: varies with the topic offered. MATH 390 GRAPH THEORY. This course will provide a friendly introduction to graph theory. The primary focus of this class is to highlight the importance of graph theory in modern mathematics. Topics that underscore its utility include the basic properties of graphs, invariants of graphs, common families of graphs, adjacency matrix of a graph and its properties, colorings, connectivity, trees, forests and spanning trees. MATH 390 INTRODUCTION TO MATH FINANCE I: STOCHASTIC CALCULUS IN DISCRETE TIME. This course will provide a friendly introduction to mathematical finance by focusing on the problem of pricing derivatives within the relatively simple framework of the binomial asset pricing model. It should provide the student with a solid understanding of basic concepts from math finance such as arbitrage, option pricing, risk-neutral measures, and hedging. At the same time, various concepts from probability will be developed, including martingales, Markov processes, and random walks. This course is recommended for any math or business/finance student who is considering work in quantitative finance, or who is simply curious about how rigorous mathematics can be applied to real-world financial problems. MATH 390 COMPLEX VARIABLES. An introduction to the theory of functions of a complex variable. Topics include the geometry of the complex plane, analytic functions, Taylor and Laurent series expansions, complex integration, and residue theory. The focus of the class will be on computation. However, some theory as well as some interesting applications to boundary value problems will be included. MATH 390 LINEAR OPTIMIZATION. Linear Optimization is concerned with methods to allocate limited resources in an optimal way. Linear constraints are imposed on variables representing those resources. Among the variable values satisfying the restrictions, those that maximize or minimize a linear function of the unknowns are looked for. The Simplex Method, an algorithm to solve linear programs will be discussed. Several applications of interest for mathematics or computer science students will be presented: production processes, allocation of personnel and other scheduling problems, transportation problems, diet problems, among others.
0.000 TO 4.000 Credit hours
0.000 TO 4.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Mathematics Department

Must be enrolled in one of the following Levels:     


General Requirements:
Course or Test: MATH 121
Minimum Grade of D
May not be taken concurrently.
Course or Test: MATH 253
Minimum Grade of D
May not be taken concurrently.  )
Course or Test: BADM 225
Minimum Grade of D
May not be taken concurrently.
Course or Test: MATH 121
Minimum Grade of D
May not be taken concurrently. )

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