 (303) (LecLabCredit Hours) This course is an introduction to the basic ideas of precalculus and calculus for the people who need preparation or review before taking more advanced courses. The exact content depends upon the particular needs of those enrolled and the requirements of degree programs they are pursuing. Topics covered will be selected from the following: algebra, functions, and graphs; slopes and secant lines; derivatives; chain rule; optimization; curve sketching; integration; the exponential and natural logarithm; and probability density functions and integration by parts.
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 (303) (LecLabCredit Hours) This course provides the necessary mathematical prerequisites for the computer science master’s program and also serves as a foundation for further study in mathematics. The topics covered include prepositional calculus: predicates and quantifiers; elementary number theory and methods of proof; mathematical induction; elementary set theory; combinatorics; functions and relations; countability; recursion and Onotation. Applications to computer science are stressed.
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 (303) (LecLabCredit Hours) Topics include basic discrete probability, including urn models and random mappings; a brief introduction to information theory; elements of number theory, including the prime number theorem, the Euler phi function, the Euclidean algorithm, and the Chinese remainder theorem; and elements of abstract algebra and finite fields including basic fundamentals of groups, rings, polynomial rings, vector spaces, and finite fields. Carries credit toward the Applied Mathematics degree only when followed by CS 668. Recommended for highlevel undergraduate students.
Prerequisites: MA 502 Mathematical Foundations of Computer Science (303)(LecLabCredit Hours) This course provides the necessary mathematical prerequisites for the computer science master’s program and also serves as a foundation for further study in mathematics. The topics covered include prepositional calculus: predicates and quantifiers; elementary number theory and methods of proof; mathematical induction; elementary set theory; combinatorics; functions and relations; countability; recursion and Onotation. Applications to computer science are stressed. Close 
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 (303) (LecLabCredit Hours) Elementary mathematical techniques important to applied mathematics. Topics covered include review of functions and continuity; ordinary and partial derivatives; integration; ordinary and partial differential equations; infinite series and numerical techniques for solving differential equations; and multiple integration and surface integrals. Applications to problems of applied mathematics are given where feasible.
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 (303) (LecLabCredit Hours) This course is primarily for students interested in using numerical methods to solve problems in mathematics, science, engineering, and management. Computational projects will be a significant part of this course and it is expected that students already have experience programming in at least one high level language. Standard topics include numerical solutions of ordinary and partial differential equations, techniques in numerical linear algebra, the Fast Fourier Transform, optimization methods, and an introduction to parallel programming. Additional topics will depend on the interests of the instructor and students.
Prerequisites: MA 232 Linear Algebra (303)(LecLabCredit Hours) This course introduces basic concepts of linear algebra from a geometric point of view. Topics include the method of Gaussian elimination to solve systems of linear equations; linear spaces and dimension; independent and dependent vectors; norms, inner product, and bases in vector spaces; determinants, eigenvalues and eigenvectors of matrices; symmetric, unitary, and normal matrices; matrix representations of linear transformations and orthogonal projections; the fundamental theorems of linear algebra; and the leastsquares method and LUdecomposition. Prerequisites: Sophomore or higher class standing. Close 
MA 346 Numerical Methods (303)(LecLabCredit Hours) This course begins with a brief introduction to writing programs in a higher level language, such as Matlab. Students are taught fundamental principles regarding machine representation of numbers, types of computational errors, and propagation of errors. The numerical methods include finding zeros of functions, solving systems of linear equations, interpolation and approximation of functions, numerical integration and differentiation, and solving initial value problems of ordinary differential equations. Close 
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 (303) (LecLabCredit Hours) Review of limits, continuity, partial differentiation, Leibnitz’s rule; implicit functions and Jacobians; gradients, divergence, curl, line and surface integrals; theorems of Stokes, Gauss and Green; complex numbers, elementary functions, analytic functions, complex integration, power series, residue theorem, evaluation of real definite integrals; systems of linear equations, rank, eigenvalues and eigenvectors.
Prerequisites: MA 227 Multivariable Calculus (303)(LecLabCredit Hours) Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Close 
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 (303) (LecLabCredit Hours) Review of first order and second order constant coefficient differential equations, nonhomogeneous equations; series solutions, Bessel and Legendre functions; boundary value problems, FourierBessel series and separation of variables for partial differential equations; classification of partial differential equations; Laplace transform methods; calculus of variations; introduction to finitedifference methods.
Prerequisites: MA 227 Multivariable Calculus (303)(LecLabCredit Hours) Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Close 
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 (303) (LecLabCredit Hours) Difference equations; calculus of variations; integral equations; and applications to engineering and science.
Prerequisites: MA 227 Multivariable Calculus (303)(LecLabCredit Hours) Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Close 
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 (303) (LecLabCredit Hours) Sample space, events, and probability; basic counting techniques and combinatorial probability; random variables, discrete and continuous; probability mass, probability density, and cumulative distribution functions; expectation and moments; some common distributions; jointly distributed random variables, conditional distributions and independence, bivariate normal, and transformations of variables; and Central Limit Theorem. Some additional topics may include an introduction to confidence intervals and hypothesis testing.
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 (303) (LecLabCredit Hours) This course offers an introduction to exploratory data analysis and the use of basic statistical tools. Topics will include: data collection; descriptive statistics, and graphical and tabular treatment of quantitative, qualitative, and count data; detecting relations between variables; confidence intervals and hypothesis testing for one and two samples; simple and multiple linear regression; analysis of variance; design of experiments; and nonparametric methods. Selected topics, such as quality control and time series analysis, may also be included. Statistical software will be used throughout the course and statistical inference will be based on examples using real data. Students will participate in group projects of data analysis. They will be trained in the different phases of the professional statistician’s work, namely: data collection, description, analysis, testing, and presentation of the conclusions.
Prerequisites: MA 540 Introduction to Probability Theory (303)(LecLabCredit Hours) Sample space, events, and probability; basic counting techniques and combinatorial probability; random variables, discrete and continuous; probability mass, probability density, and cumulative distribution functions; expectation and moments; some common distributions; jointly distributed random variables, conditional distributions and independence, bivariate normal, and transformations of variables; and Central Limit Theorem. Some additional topics may include an introduction to confidence intervals and hypothesis testing. Close 
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 (303) (LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
Prerequisites: MA 227 Multivariable Calculus (303)(LecLabCredit Hours) Review of matrix operations, Cramer’s rule, row reduction of matrices; inverse of a matrix, eigenvalues and eigenvectors; systems of linear algebraic equations; matrix methods for linear systems of differential equations, normal form, homogeneous constant coefficient systems, complex eigenvalues, nonhomogeneous systems, the matrix exponential; double and triple integrals; polar, cylindrical and spherical coordinates; surface and line integrals; integral theorems of Green, Gauss and Stokes. Close 
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 (303) (LecLabCredit Hours) A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, RiemannStieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis.
Prerequisites: MA 547 Advanced Calculus I (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes. Close 
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 (303) (LecLabCredit Hours) Fields and vector spaces; subspaces and quotient spaces; basis and dimension; linear transformations and matrices; determinants; and the theory of a single linear transformation.
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 (303) (LecLabCredit Hours) Special topics in mathematics not covered in regularly scheduled courses and suitable for both graduates and advanced undergraduates. May be taken more than once.
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 (303) (LecLabCredit Hours) A unified development of mathematical tools for treating a variety of problems in physics and engineering. Linear algebra, normed and inner product spaces, and spectral theory of operators; integral equations; boundary value problems for ordinary and partial differential equations; Green’s functions; calculus of variations; and other related topics as time permits. Problem solving is stressed.
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 (003) (LecLabCredit Hours) A unified development of mathematical tools for treating a variety of problems in physics and engineering; linear algebra, normed and inner product spaces, spectral theory of operators; integral equations; boundary value problems for ordinary and partial differential equations; Green's functions; calculus of variations; other related topics as time permits; problem solving is stressed.
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 (303) (LecLabCredit Hours)
Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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 (303) (LecLabCredit Hours) Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
Prerequisites: MA 605 Foundations of Algebra I (303)(LecLabCredit Hours)
Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory. Close 
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 (303) (LecLabCredit Hours) Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems.
Prerequisites: MA 222 Probability and Statistics (303)(LecLabCredit Hours) Introduces the essentials of probability theory and elementary statistics. Lectures and assignments greatly stress the manifold applications of probability and statistics to computer science, production management, quality control, and reliability. A statistical computer package is used throughout the course for teaching and for assignments. Contents include: descriptive statistics, pictorial and tabular methods, and measures of location and of variability; sample space and events, probability axioms, and counting techniques; conditional probability and independence, and Bayes' formula; discrete random variables, distribution functions and moments, and binomial and Poisson distributions; continuous random variables, densities and moments, normal, gamma, and exponential and Weibull distributions unions; distribution of the sum and average of random samples; the Central Limit Theorem; confidence intervals for the mean and the variance; hypothesis testing and pvalues, and applications for the mean; simple linear regression, and estimation of and inference about the parameters; and correlation and prediction in a regression model. Close 
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 (303) (LecLabCredit Hours) Point estimation, method of moments, maximum likelihood, and properties of point estimators; confidence intervals and hypothesis testing; sufficiency; NeymanPearson theorem, uniformly most powerful tests, and likelihood ratio tests; and Fisher information and the CramerRao inequality. Additional topics may include nonparametric statistics, decision theory, and linear models.
Prerequisites: MA 611 Probability (303)(LecLabCredit Hours) Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems. Close 
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 (303) (LecLabCredit Hours) The MA 615616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimummaximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers. Corequisites: MA 547 Advanced Calculus I (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes. Close 
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 (303) (LecLabCredit Hours)
The MA 615616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimummaximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers.
Prerequisites: MA 615 Numerical Analysis I (303)(LecLabCredit Hours) The MA 615616 sequence covers topics in numerical analysis and numerical methods including: errors and accuracy; polynomial approximation; interpolation; numerical differentiation and integration; numerical solution of differential equations; least square and minimummaximum error approximations; nonlinear equations; simultaneous linear equations; summing series, Fourier series, filter design, the frequency approach, design of numerical tools, and statistics of error analysis; eigenvalues and eigenvectors of matrices; and the orientation throughout is toward computers. Close 
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 (303) (LecLabCredit Hours) This course covers basic ideas in sampling theory and uses only elementary mathematics. Topics include multistage sampling, stratified sampling, systematic sampling, selfweighting samples, and optimum allocation.
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 (303) (LecLabCredit Hours) Random walks and Markov chains; Brownian motions and Markov processes; and applications, stationary (wide sense) processes, infinite divisibility, and spectral decomposition. By permission of instructor.
Prerequisites: MA 611 Probability (303)(LecLabCredit Hours) Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems. Close 
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 (303) (LecLabCredit Hours) Absolute geometry as founded on axioms of incidence, order, congruence, and continuity; models of absolute geometry and problems of consistency; independence and categoricity of an axiom system; Euclidean and nonEuclidean geometry; brief description of the Erlangen program; and classical differential geometry of surfaces.
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 (303) (LecLabCredit Hours) Fundamental laws of counting, permutations, combinations, recurrence relations, Mšbius inversion, probleme des menages, probleme des recontres, partitions, trees, generating functions, Ramsey theory, transversal theory, and matroid theory.
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 (303) (LecLabCredit Hours) The objective of this course is to introduce the students to the basic results of convex analysis and optimization. The properties of nonlinear nonsmooth optimization models will be analyzed. Topics include: separation and representation of convex sets, properties of convex functions, subgradients, optimality conditions, saddle points, constraint qualifications, Fenchel and Lagrange duality, and sensitivity analysis. Examples of optimization models from probability, statistics, and approximation theory will be discussed, as well as some basic models from management, finance, telecommunications, and other fields.
Prerequisites: MA 547 Advanced Calculus I (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes. Close 
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 (303) (LecLabCredit Hours) The objective of this course is to introduce the students to the most popular numerical methods for solving nonlinear and nonsmooth optimization problems. The techniques will be based on the properties of nonlinear nonsmooth optimization models and optimality conditions. Linear optimization techniques will be treated as a special case. Some emphasis will be put on using optimization software. Examples using AMPL and CPLEX will be demonstrated in class. Topics include line search, nonderivative methods, basic decent methods, conjugate gradient methods, subgradient methods, Newton methods, projection methods, penalty, barrier, interior point methods, Lagrangian methods, bundle methods, trustregion method, numerical treatment of nonconvex models, and decomposition methods.
Prerequisites: MA 629 Convex Analysis and Optimization (303)(LecLabCredit Hours) The objective of this course is to introduce the students to the basic results of convex analysis and optimization. The properties of nonlinear nonsmooth optimization models will be analyzed. Topics include: separation and representation of convex sets, properties of convex functions, subgradients, optimality conditions, saddle points, constraint qualifications, Fenchel and Lagrange duality, and sensitivity analysis. Examples of optimization models from probability, statistics, and approximation theory will be discussed, as well as some basic models from management, finance, telecommunications, and other fields. Close 
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 (303) (LecLabCredit Hours) Strategic games and Nash equilibrium, strictly competitive (zerosum) games and maxminimization, sStrategic games with imperfect information (Bayesian games), extensive games with perfect information (bargaining and repeated games), extensive games with imperfect information and signaling games, coalitional games (the core, stable sets, and bargaining sets), and auctions.
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 (303) (LecLabCredit Hours) Modern theory of the delta function and other generalized functions: Fourier and Laplace transforms and applications to ordinary and partial differential equations.
Prerequisites: MA 548 Advanced Calculus II (303)(LecLabCredit Hours) A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, RiemannStieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis. Close 
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 (303) (LecLabCredit Hours) Queuing theory, transportation problem, traffic theory, inventory control, search theory, and methods of optimization.
Prerequisites: MA 540 Introduction to Probability Theory (303)(LecLabCredit Hours) Sample space, events, and probability; basic counting techniques and combinatorial probability; random variables, discrete and continuous; probability mass, probability density, and cumulative distribution functions; expectation and moments; some common distributions; jointly distributed random variables, conditional distributions and independence, bivariate normal, and transformations of variables; and Central Limit Theorem. Some additional topics may include an introduction to confidence intervals and hypothesis testing. Close 
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 (303) (LecLabCredit Hours) The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or modern approach.
Prerequisites: MA 548 Advanced Calculus II (303)(LecLabCredit Hours) A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, RiemannStieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis. Close 
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 (303) (LecLabCredit Hours) Lp spaces and applications to Fourier series and LebesqueStieltjes integral.
Prerequisites: MA 635 Real Variables I (303)(LecLabCredit Hours) The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or modern approach. Close 
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 (303) (LecLabCredit Hours) Prepositional calculus; syntax and semantics of first order theories; completeness theorem; elementary model theory: axiomatic development of ZermeloFraenkel or BernaysGödel set theory; and ordinals, cardinals, the axiom of choice, and several equivalent axioms.
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 (303) (LecLabCredit Hours) First order number theory; primitive and general recursive functions; arithmetization; Gödel’s incompleteness theorems; Tarski’s theorems; and syntax and semantics of second order theories.
Prerequisites: MA 637 Mathematical Logic I (303)(LecLabCredit Hours) Prepositional calculus; syntax and semantics of first order theories; completeness theorem; elementary model theory: axiomatic development of ZermeloFraenkel or BernaysGödel set theory; and ordinals, cardinals, the axiom of choice, and several equivalent axioms. Close 
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 (303) (LecLabCredit Hours) Scope and applications of time series analysis: process control, financial data analysis and forecasting, and signal processing. Exploratory data analysis: graphical analysis, trend and seasonality detection and removal, and movingaverage filtering. Review of basic statistical concepts related to the characterization of stationary processes. ARMA models and prediction of stationary processes. Estimation of ARMA models and model building and forecasting with ARMA models. Spectral analysis: periodogram testing for seasonality and periodicities and the maximum entropy and maximumlikelihood estimators. Asymptotic convergence. Selected topics, such as multivariate time series, nonlinear models, Kalman filtering, econometric forecasting, and longmemory processes. Selected applications, such as the unitroot problem in economics, forecasting and testing for market efficiency in financial time series, process control, and quality control.
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  (003) (LecLabCredit Hours) Scope and applications of time series analysis: process control, financial data analysis and forecasting, signal processing. Exploratory data analysis: graphical analysis, trend and seasonality detection and removal, movingaverage filtering. Review of basic statistical concepts related to the characterization of stationary processes. ARMA models, prediction of stationary processes. Estimation of ARMA models, model building and forecasting with ARMA models. Spectral analysis: periodogram testing for seasonality and periodicities, the maximum entropy and maximumlikelihood estimators. A symptotic convergence. Selected topics such as multivariate time series, nonlinear models, Kalman filtering, econometric forecasting, and longmemory processes. Selected applications such as the unitroot problem in economics, forecasting and testing for market efficiency in financial time series, process control and quality control.
Prerequisites: MA 641 (303)(LecLabCredit Hours) Scope and applications of time series analysis: process control, financial data analysis and forecasting, and signal processing. Exploratory data analysis: graphical analysis, trend and seasonality detection and removal, and movingaverage filtering. Review of basic statistical concepts related to the characterization of stationary processes. ARMA models and prediction of stationary processes. Estimation of ARMA models and model building and forecasting with ARMA models. Spectral analysis: periodogram testing for seasonality and periodicities and the maximum entropy and maximumlikelihood estimators. Asymptotic convergence. Selected topics, such as multivariate time series, nonlinear models, Kalman filtering, econometric forecasting, and longmemory processes. Selected applications, such as the unitroot problem in economics, forecasting and testing for market efficiency in financial time series, process control, and quality control.
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 (303) (LecLabCredit Hours) Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finitedimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and PoincareBendixon theorem. Corequisites: MA 547 Advanced Calculus I (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes. Close 
Prerequisites: MA 232 (303)(LecLabCredit Hours) This course introduces basic concepts of linear algebra from a geometric point of view. Topics include the method of Gaussian elimination to solve systems of linear equations; linear spaces and dimension; independent and dependent vectors; norms, inner product, and bases in vector spaces; determinants, eigenvalues and eigenvectors of matrices; symmetric, unitary, and normal matrices; matrix representations of linear transformations and orthogonal projections; the fundamental theorems of linear algebra; and the leastsquares method and LUdecomposition. Prerequisites: Sophomore or higher class standing.
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 (303) (LecLabCredit Hours) This course discusses the classical theory and applications of partial differential equations and introduces the student to the modern theory. Classification of second order equations; wellposedness; existence and uniqueness for the Cauchy problem; Riemann function; Dirichlet and Neumann problems; Green’s functions; perturbation theory; elliptic operators; variational formulation for the Laplace equation; weak solutions; and Sobolev spaces. Corequisites: MA 547 Advanced Calculus I (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes. Close 
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 (303) (LecLabCredit Hours) Metric spaces and topological spaces, bases and subbases, connectivity, local (path) connectivity, separation axioms, compactness and local compactness, concepts of convergence, Tychonoff’s theorem, Urysohn’s lemma, Tietze extension theorem, and selected topics as time permits.
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 (003) (LecLabCredit Hours)
Metric spaces and topological spaces, bases and subbases, connectivity, local (path) connectivity, separation axioms, compactness and local compactness, concepts of convergence, Tychonoff's theorem, Urysohn's lemma, Tietze extension theorem; homotopy type, fundamental group, covering spaces; topology of Euclidean space and manifold; selected topics as time permits. Spring semester.
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 (303) (LecLabCredit Hours) This course is an introduction to methods and theory in numerical solutions of partial differential equations. The finite difference and pseudospectral methods will be used as examples to solve partial differential equations, including parabolic, hyperbolic, and elliptic equations in one or higher dimensional space. The theory on consistency, convergence, and Von Neumann stability analysis of numerical schemes will be emphasized for a basic understanding about how to control numerical errors and to achieve higher order accuracy for numerical solutions. Students will also be assigned projects to obtain the firsthand experience in numerical computations.
Prerequisites: MA 650 (303)(LecLabCredit Hours) This course discusses the classical theory and applications of partial differential equations and introduces the student to the modern theory. Classification of second order equations; wellposedness; existence and uniqueness for the Cauchy problem; Riemann function; Dirichlet and Neumann problems; Green’s functions; perturbation theory; elliptic operators; variational formulation for the Laplace equation; weak solutions; and Sobolev spaces.
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 (303) (LecLabCredit Hours) The main purpose of this course is to present the foundations of the optimal control theory, some applications, and their solutions. The students will be introduced to the core concepts and results of control and system theory. The foundational and basic results will be derived for discrete and continuous time scales, and state variables. Topics to be covered: proportionalderivative control; statespace and spectrum assignment; outputs and dynamic feedback; reachability; controllability; feedback and stability; Lyapunov theory; linearization principle of observability; dynamic programming algorithm; multipliers for unconstrained and constrained controls; and Pontryagin maximum principle.
Prerequisites: MA 547 (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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MA 649 (303)(LecLabCredit Hours) Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finitedimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and PoincareBendixon theorem.
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 (303) (LecLabCredit Hours) The main purpose of this course is to present the foundations of the stochastic control theory, the corresponding numerical methods, and some applications. The focus will be on the idea of dynamic programming which will be developed starting from deterministic models, through finitehorizon stochastic problems, to infinitehorizon stochastic problems of various types. Applications to queuing systems, network design, and routing; supplychain management and others will be discussed in detail. Topics to be covered: basic concepts of control theory for stochastic dynamic systems; controlled Markov chains; dynamic programming for finite horizon problems; infinite horizon discounted problems; numerical methods for infinite horizon problems; linear stochastic dynamic systems in discrete time; tracking and Kalman filtering; linear quadratic models; controlled Markov processes in continuous time; and elements of stochastic control theory in continuous time and state space.
Prerequisites: MA 540 (303)(LecLabCredit Hours) Sample space, events, and probability; basic counting techniques and combinatorial probability; random variables, discrete and continuous; probability mass, probability density, and cumulative distribution functions; expectation and moments; some common distributions; jointly distributed random variables, conditional distributions and independence, bivariate normal, and transformations of variables; and Central Limit Theorem. Some additional topics may include an introduction to confidence intervals and hypothesis testing.
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MA 547 (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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MA 623 (303)(LecLabCredit Hours) Random walks and Markov chains; Brownian motions and Markov processes; and applications, stationary (wide sense) processes, infinite divisibility, and spectral decomposition. By permission of instructor.
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 (303) (LecLabCredit Hours) This course introduces students to modeling and numerical techniques for optimization under uncertainty and risk. Topics include: generalized concavity of measures, optimization problems with probabilistic constraints (convexity, differentiability, optimality, and duality), numerical methods for solving problems with probabilistic constraints, twostage and multistage models (structure, optimality, duality), decomposition methods for twostage and multistage models, risk averse optimization models,
Prerequisites: MA 547 (303)(LecLabCredit Hours) Elementary topology of Euclidean spaces; differential calculus of functions of several variables; inverse and implicit function theorems; integration; differential forms; and theorems of Gauss, Green, and Stokes.
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MA 629 (303)(LecLabCredit Hours) The objective of this course is to introduce the students to the basic results of convex analysis and optimization. The properties of nonlinear nonsmooth optimization models will be analyzed. Topics include: separation and representation of convex sets, properties of convex functions, subgradients, optimality conditions, saddle points, constraint qualifications, Fenchel and Lagrange duality, and sensitivity analysis. Examples of optimization models from probability, statistics, and approximation theory will be discussed, as well as some basic models from management, finance, telecommunications, and other fields.
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MA 649 (303)(LecLabCredit Hours) Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finitedimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and PoincareBendixon theorem.
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 (303) (LecLabCredit Hours) Complex numbers; elementary functions; Möbius transformations; analytic functions; power series; integration; CauchyGoursat theorems; Cauchy integral formula; Taylor and Laurent series; singularities; residue theory; and meromorphic and entire functions.
Prerequisites: MA 548 (303)(LecLabCredit Hours) A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, RiemannStieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis.
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 (003) (LecLabCredit Hours) Analytic continuation; Riemann surfaces; elliptic functions; gamma function; conformal mapping.
Prerequisites: MA 681 (303)(LecLabCredit Hours) Complex numbers; elementary functions; Möbius transformations; analytic functions; power series; integration; CauchyGoursat theorems; Cauchy integral formula; Taylor and Laurent series; singularities; residue theory; and meromorphic and entire functions.
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 (303) (LecLabCredit Hours) Theory and methods in continuous and discrete dynamical systems. Topics may vary, but will typically include local bifurcation theory for vector fields and maps, center manifold reductions, normal forms, periodic orbits and Poincaré maps, averaging methods, Melnikov methods, chaotic dynamics, the Smale horseshoe map, and symbolic dynamics.
Prerequisites: MA 649 (303)(LecLabCredit Hours) Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finitedimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and PoincareBendixon theorem.
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 (303) (LecLabCredit Hours) Study of the classical transforms, the Laplace, Fourier, Hilbert, and other transforms; inversion and application to solution of differential, difference, and integral equations; and Abelian and Tauberian theorems, including Wiener’s theory.
Prerequisites: MA 632 (303)(LecLabCredit Hours) Strategic games and Nash equilibrium, strictly competitive (zerosum) games and maxminimization, sStrategic games with imperfect information (Bayesian games), extensive games with perfect information (bargaining and repeated games), extensive games with imperfect information and signaling games, coalitional games (the core, stable sets, and bargaining sets), and auctions.
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MA 681 (303)(LecLabCredit Hours) Complex numbers; elementary functions; Möbius transformations; analytic functions; power series; integration; CauchyGoursat theorems; Cauchy integral formula; Taylor and Laurent series; singularities; residue theory; and meromorphic and entire functions.
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MA 682 (003)(LecLabCredit Hours) Analytic continuation; Riemann surfaces; elliptic functions; gamma function; conformal mapping.
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 (303) (LecLabCredit Hours) Geometry of Hilbert space; spectral theory of selfadjoint and normal operators; applications to differential operators; multiplicity theory; and families of operators, Stone’s theorem, and introduction to rings of operators.
Prerequisites: MA 635 (303)(LecLabCredit Hours) The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or modern approach.
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MA 636 (303)(LecLabCredit Hours) Lp spaces and applications to Fourier series and LebesqueStieltjes integral.
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MA 681 (303)(LecLabCredit Hours) Complex numbers; elementary functions; Möbius transformations; analytic functions; power series; integration; CauchyGoursat theorems; Cauchy integral formula; Taylor and Laurent series; singularities; residue theory; and meromorphic and entire functions.
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MA 682 (003)(LecLabCredit Hours) Analytic continuation; Riemann surfaces; elliptic functions; gamma function; conformal mapping.
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 (003) (LecLabCredit Hours) This course introduces basic concepts and techniques to solve inverse problems for both integral and differential equations. Topics include: Illposed problems, Tikhonov regularization, collocation methods, Galerkin methods, inverse eigenvalue problems, inverse boundary value problems, conditions on dense solvability. Computational projects may be assigned.
Prerequisites: MA 548 (303)(LecLabCredit Hours) A continuation of MA 547, but with greater emphasis on mathematical rigor. Topics covered may include convergence of series, RiemannStieltjes integration, functions of bounded variation, metric spaces, introduction to measure theory, and functional analysis.
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 (303) (LecLabCredit Hours) The course will introduce the students to the fundamental mathematical models of risk and approaches to decisionmaking under uncertainty and riskaversion. The mathematical models will range from classical models as Expected Utility Theory, Prospect Theory, Dual Utility Theory, to stateoftheart work on stochastic dominance, the theory of coherent risk measures, and general deviation measures. The course also surveys recent developments in particular applied areas as portfolio optimization, asset pricing, nuclear safety, reliability, etc.
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 (303) (LecLabCredit Hours) Linear topological spaces, local convexity, and spaces of distribution; Banach spaces; three fundamental theorems and applications to classical analysis; operators, operational calculus, compact operators, and applications to integral equations; KleinMilman theorems; and fixed point theorems with applications to nonlinear problems.
Prerequisites: MA 635 (303)(LecLabCredit Hours) The real number system. Introduction to metric spaces and their applications. Lebesque measure and integral from a classical and/or modern approach.
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 (303) (LecLabCredit Hours) Notion of simplicial complex, absolute, and relative homology groups of a space; exact sequences; cohomology; axioms for homology theory; introduction to homological algebra; and homotopy and the fundamental group.
Prerequisites: MA 605 (303)(LecLabCredit Hours)
Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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MA 651 (303)(LecLabCredit Hours) Metric spaces and topological spaces, bases and subbases, connectivity, local (path) connectivity, separation axioms, compactness and local compactness, concepts of convergence, Tychonoff’s theorem, Urysohn’s lemma, Tietze extension theorem, and selected topics as time permits.
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 (003) (LecLabCredit Hours) Martingales; generalized weak and strong laws; infinitely divisible distribution; stable distributions, limiting distributions for triangular arrays; semigroup theory applications; bilateral Laplace transforms; renewal equation; random walks;. Markov processes.
Prerequisites: MA 611 (303)(LecLabCredit Hours) Foundations of probability, random variables and their distributions, discrete and continuous random variables, independence, expectation and conditioning, generating functions, multivariate distributions, convergence of random variables, and classical limit theorems.
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 (003) (LecLabCredit Hours) Selected topics may include: distribution theory; theory of inference; foundations of probability; spectral analysis; multivariant analysis.
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 (303) (LecLabCredit Hours) Existence and uniqueness of solutions; dependence on parameters; periodic solutions; nonlinear autonomous systems; PoincareBendixon theory; continuous transformation groups; linear systems; Floquet theory; linear systems in complex domain; regular and irregular singularities; asymptotic expansions; Stokes' phenomenon; boundary value problems.
Prerequisites: MA 649 (303)(LecLabCredit Hours) Theory and application of ordinary differential equations (ODEs) with an emphasis on ODEs as continuous dynamical systems on a finitedimensional phase space. Standard topics include existence and uniqueness theorems, general theory for linear equations, the exponential of linear map, stability of equilibrium points, hyperbolicity and structural stability, Lyapunov’s method, invariant manifolds, Floquet theory for periodic orbits, and PoincareBendixon theorem.
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 (303) (LecLabCredit Hours) Characteristics and classification of equations; CauchyKowalewski theorem; linear and quasilinear systems; elliptic equations and potential theory; Green's function; mean value theorems; a priori estimates; functions space methods; hyperbolic equations; Riemann's solution of the Cauchy problem; discontinuities and shocks; Huyghen's principle; method of spherical means; parabolic equations.
Prerequisites: MA 650 (303)(LecLabCredit Hours) This course discusses the classical theory and applications of partial differential equations and introduces the student to the modern theory. Classification of second order equations; wellposedness; existence and uniqueness for the Cauchy problem; Riemann function; Dirichlet and Neumann problems; Green’s functions; perturbation theory; elliptic operators; variational formulation for the Laplace equation; weak solutions; and Sobolev spaces.
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 (003) (LecLabCredit Hours) Selected topics in numerical analysis not treated in MA615616; topics may include: numerical solution of partial differential equations, boundary value problems, approximation theory; Monte Carlo methods, power spectral methods as they apply to numerical analysis, optimal search problems.
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 (303) (LecLabCredit Hours) Algebraic number fields; rings of algebraic integers and integral basis of field discriminant; unique factorication for ideals; splitting and ramifications of primes; Kummer’s theorem with applications to quadratic and roots of unity fields; padic numbers; Hensel’s lemMA ; geometry of numbers; units in an algebraic extension; finiteness of class numbers of a field; and computation of class numbers in special cases.
Prerequisites: MA 605 (303)(LecLabCredit Hours)
Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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MA 606 (303)(LecLabCredit Hours) Topics covered in the sequence MA 605606 include: elementary number theory, basic group theory, Lagrange’s theorem, isomorphism theorems, solvability, direct products, JordanHolder theorem, Sylow theorems, basic properties of rings, quotient rings, field of quotients of an integral domain, polynomial rings, factorization, elementary properties of fields, field extensions, and Galois theory.
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 (003) (LecLabCredit Hours) Selected topics in advanced analysis not treated in other courses; topics may include: integral transforms, general convolution transform, approximation theory, theorems of Jackson and Bernstein, functions of exponential type, Nevalinna's theory of meromoporhic functions, asymptotic development, perturbation theory.
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 (003) (LecLabCredit Hours) Selected topics in algebra not treated in other courses; topics may include: group representations, Lie algebra, structure of rings, valuation theory, algebraic curves, Galois theory of noncommutative fields, polynomial ideals, elimination theory.
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 (003) (LecLabCredit Hours) Selected topics in mathematical logic; topics may include: a study of the connection between the semantical and syntactical treatments of propositional calculus and quantification theory, including references to the works of Harbrand, Dreben and Hintikka, Gödel's completeness for theorem for the first order and predicate calculus, recursive function theory, decidable theories, and Gödel's incompleteness theorem for arithmetic, axiomatic set theory, model theory.
Prerequisites: MA 637 (303)(LecLabCredit Hours) Prepositional calculus; syntax and semantics of first order theories; completeness theorem; elementary model theory: axiomatic development of ZermeloFraenkel or BernaysGödel set theory; and ordinals, cardinals, the axiom of choice, and several equivalent axioms.
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MA 638 (303)(LecLabCredit Hours) First order number theory; primitive and general recursive functions; arithmetization; Gödel’s incompleteness theorems; Tarski’s theorems; and syntax and semantics of second order theories.
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 (003) (LecLabCredit Hours) Selected topics in topology; topics may include: K theory, infinite dimensional analysis, knot theory, applications of algebraic topology to algebraic geometry.
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 (003) (LecLabCredit Hours) This course will focus on one or more topics of current interest in graph theory and its applications. Possible topics include: linear algebra and graph theory; graphs and groups, graphical enumeration; extremal graph theory; graph equations; covering and packing problems; graph algorithms; graph
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 (003) (LecLabCredit Hours) Existence and uniqueness of solutions to nonlinear partial differential equations with applications to equations from physics and engineering. Topics covered will include Degree Theory, The Mountain Pass Lemma, Variational Methods, Index Theory, NashMoser Iteration Schemes. The course will also include a review of Hilbert space methods.
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 (003) (LecLabCredit Hours) One to six credits. Limit of six credits for the degree of Master of Science.
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 (003) (LecLabCredit Hours) One to six credits. Limit of six credits for the degree of Doctor of Philosophy.
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 (303) (LecLabCredit Hours) Special topics in mathematics not covered in regularly scheduled courses and suitable for both graduates and advanced undergraduates. May be taken more than once.
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 (003) (LecLabCredit Hours) For the degree of Master of Science. Five to ten credits with departmental approval.
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 (003) (LecLabCredit Hours) Original research carried out under the guidance of a member of the faculty which may serve as the basis for the dissertation required for the degree of Doctor of Philosophy. Hours and credits to be arranged.
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