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MATH 551. Real Variables 1.

Credit Hours: 
3
Semester Offered: 
Comments From Graduate Director: 
This is the first semester of a basic graduate two-semester course (551/651) in real analysis. Real analysis is one of the areas of the M.S. Advanced Exams/Ph.D. entrance exams and the full-year sequence should be taken if preparing for the exam. It is a prerequisite for the doctoral sequence in functional analysis and other doctoral-level courses in analysis and applied mathematics. You should have a good background in advanced calculus (Math 451 at least) before taking this class. The first semester is largely devoted to developing Lebesgue measure. Math 651, Real Variables II, is offered in the spring.

MATH 555. Complex Variables 1.

Credit Hours: 
3
Semester Offered: 
Comments From Graduate Director: 
This course is offered every other year and provides a graduate-level introduction to complex variables. Math 451 is generally an expected prerequisite. A basic knowledge of complex variables, at least at an undergraduate level, is essential in many areas of pure and applied mathematics so if you have no prior background and you have taken a course similar to Math 451, you might want to consider taking this course. Otherwise, we offer an undergraduate course Math 456 each spring which in most cases does not count toward course work requirements but will give you a working knowledge of the area. Also Math 568 covers basic complex variables from an engineering mathematics viewpoint.

MATH 557. Calculus Of Variations.

Credit Hours: 
3

MATH 561. Geometric Modeling-Curves/Surf.

Credit Hours: 
3

MATH 563. Mathematics Modeling.

Credit Hours: 
3
Semester Offered: 
Comments From Graduate Director: 
This course will give the student some exposure to how mathematics is used to analyze problems arising in real-world applications in industry and science. It is a required course in Option B of the M.S. program. It has been run on a yearly basis, concurrently with Math 464. Students will need a basic undergraduate background in the areas of differential equations and probability and statistics, and basic knowledge of computing software such as Excel or Matlab.

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