Convex sets, linear inequalities, linear programming, two-person games, finite graphs. Applications in management, economics, and behavioral sciences.

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Limits, continuity, derivatives, antiderivatives, the definite integral.

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Limits, continuity, derivatives, antiderivatives and definite integrals; applications to optimization, physical and life science models. Lab includes web-based practice and evaluation.

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Techniques of integration, exponential and logarithm functions, sequences and series, polar coordinates.

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This class is for freshmen who have earned a 4 or 5 on the AP AB exam, or a 5 on the IB HL exam. Topics include: techniques of integration, exponential and logarithm functions, sequences and series, and polar coordinates.

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Integration, differential equations, multivariable calculus, and discrete probability and statistics, with an emphasis on applications to biology.

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Topics will be announced each semester when class is scheduled.

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Development and use of mathematical models from probability and statistics with applications.

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Vectors; multivariable functions; partial derivatives; multiple integrals; vector and scalar fields; Green's and Stokes' theorems; divergence theorem.

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This is a standard first semester Differential Equations course which covers first and second-order differential equations and systems of differential equations, with an emphasis placed on developing techniques for solving differential equations.

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Systems of linear equations, matrices, determinants, linear transformations, eigenvalues and eigenvectors, least-squares.

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An introduction to theoretical mathematics. Logic and proofs, operations on sets, induction, relations, functions.

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Topics in the history of mathematics and their philosophical background. Genesis and evolution of ideas in analysis, algebra, geometry, mechanics, foundations. Historical and philosophical aspects of concepts of infinity, mathematical rigor, probability, etc.

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Topics in the history of mathematics and their philosophical background. Genesis and evolution of ideas in analysis, algebra, geometry, mechanics, foundations. Historical and philosophical aspects of concepts of infinity, mathematical rigor, probability, etc.

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This course is the first half of the advanced math introductory sequence. It covers the basics of linear algebra: vector spaces, linear transformations, determinants, and eigenvalues, with an emphasis on mathematical rigor. This class is for freshmen who scored a 5 on the Calculus AP BC exam.

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This course is the second half of the advanced mathematics introductory sequence. It covers the basics of vector calculus: differentiable mappings, differential forms, and integration theory.

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Rotating topics in mathematics. May be repeated for credit when the topic varies. Pre and co requisites depend on the topic offered.

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May be repeated for credit, total credit not to exceed six hours. Cannot be used to meet course requirements for a Math major or minor. Topics vary by instructor.

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Solution of linear and nonlinear systems of equations, interpolation, least-squares approximation, numerical integration, and differentiation.

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Analytic functions, elementary functions, integrals, power series, residues, and conformal mapping.

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Axiomatic treatment of vector spaces, inner product spaces, minimal polynomials, Cayley Hamilton theorem, Jordan form, and bilinear forms.

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This course introduces the basic concepts of algebraic and analytic number theory. Topics include: congruence relations, the distribution of prime numbers, quadratic reciprocity, Diophantine equations, continued fractions, and generating functions.

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Combinations and permutations, counting techniques, recurrence relations, and generating functions. Block designs, finite planes, and coding theory. Introduction to graph theory.

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Curves and surfaces in 3-space. The geometry of the Gauss map. Special surfaces. The intrinsic geometry of surfaces. Surfaces and computer graphics.

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Principles of mathematical modeling; case studies using nonlinear ordinary differential equations, difference equations, and partial differential equations.

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Theory of linear programming, duality, optimal flows in networks, and mathematical programming.

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Nonlinear optimization problems arise in a wide range of applications, for example, in economics, physics, engineering, imaging. This introductory course covers a wide range of examples and both theory and practice of unconstrained and constrained optimization.

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PDEs and their origin, classification of PDEs, analytical methods for the solution of PDEs, qualitative properties of the solutions, eigenvalue problems and introduction to numerical methods.

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Partial Differential Equations (PDE's) are a formidable tool for describing real-life problems. In this course we use PDE's for cardiovascular problems and other real-life situations. Students will visit radiology labs and learn about image processing and numerical simulations in medicine.

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Finite and continuous probability theory, distribution models (binomial, geometric, uniform, normal, Poisson, and exponential), the Chebyshev inequality, expectation and variance, moment generating functions, the central limit theorem, and applications.

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Fundamentals of statistical inference: estimation, properties of estimators, methods for comparing estimators, confidence intervals, hypothesis testing, regression, and analysis of variance.

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Fundamentals of statistical inference: estimation, properties of estimators, methods for comparing estimators, confidence intervals, hypothesis testing, regression, and analysis of variance.This course is an extension of MATH 362 which includes a writing lab. Students take a writing lab and learn how to articulate why the statistical methods they use are applicable, discuss what their results show and make recommendations for future studies.

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Rotating topics in mathematics. May be repeated for credit when the topic varies. Pre and co requisites depend on the topic offered.

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Analysis of sets and functions in n-space which focuses on basic topological properties of sets as well as continuity and differentiation of functions. Topics: exterme value theorem, chain rule, and inverse function theorem.

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This course is a continuation of Math 411 which focuses on integration and uniform convergence in n-space. Topics include: Stoke's theorem, Fubini's theorem, Taylor's theorem, the Stone-Weierstrass theorem, and Sard's theorem.

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Groups (definition and examples), cosets, Lagrange's Theorem, symmetric and alternating groups, Cayley's Theorem, isomorphisms, Cauchy's Theorem, quotient groups and homomorphisms, and the action of a group on a set. Additional topics may include the Sylow Theorems.

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Ring Theory and Field Theory: polynomial rings, unique factorization, Euclidean domains, splitting fields of polynomials, elements of Galois theory, finite fields.

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Introduction to the use of calculus in economic analysis; comparative static problem and optimization theory; consideration of the mathematical techniques used in game theory.

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Rotating topics in mathematics. May be repeated for credit when the topic varies. Pre and co requisites depend on the topic offered.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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May be repeated for credit when topic varies.

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Normally taken in student's last semester, up to a maximum of 4 credit hours.

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Normally taken in student's last semester, up to a maximum of 4 credit hours.

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May be repeated for credit, total credit not to exceed six hours. Prerequisite: consent of instructor. Cannot be used to meet course requirements for a Math major or minor.

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