Untitled - University of New Orleans

separation of variables, eigenfunction expansions, integral transforms,
Sturm-Liouville boundary value problems, initial value
problems and boundary value problems for hyperbolic, parabolic,
and elliptic equations, fundamental solutions, maximum principle,
classical and modern applications.
MATH 4230 Finite Element Analysis
3 cr.
Prerequisites: MATH 2115, 2221 and 2511. A knowledge of Fortran or
consent of department. Variational principle, weighted residual
methods, finite element analysis of one and two dimensional steady
state and transient boundary value problems involving partial differential
equations, software development and implementations.
MATH 4230G Finite Element Analysis
3 cr.
Prerequisites: MATH 2115, 2221 and 2511. A knowledge of Fortran or
consent of department. Variational principle, weighted residual
methods, finite element analysis of one and two dimensional steady
state and transient boundary value problems involving partial differential
equations, software development and implementations.
MATH 4240 Boundary Element Method
3 cr.
Prerequisites: MATH 2115, 2221, and 2511. Some knowledge of computer
programming is also required. Weak variational formulation,
fundamental solutions, formulation of two- and three-dimensional
boundary element equations, potential problems, nonconvex regions,
linear elasticity, fluid flows, acoustics, software development.
MATH 4240G Boundary Element Method
3 cr.
Prerequisites: MATH 2115, 2221, and 2511. Some knowledge of computer
programming is also required. Weak variational formulation,
fundamental solutions, formulation of two- and three-dimensional
boundary element equations, potential problems, nonconvex regions,
linear elasticity, fluid flows, acoustics, software development.
MATH 4251 Numerical Analysis
3 cr.
Prerequisite: MATH 2115 or consent of department. Numerical
solution of systems of linear and nonlinear equations; interpolation,
approximation, and minimization of functions; numerical
integration.
MATH 4251G Numerical Analysis
3 cr.
Prerequisite: MATH 2115 or consent of department. Numerical
solution of systems of linear and nonlinear equations; interpolation,
approximation, and minimization of functions; numerical
integration.
MATH 4252 Numerical Analysis
3 cr.
Prerequisites: MATH 2221 and 4251, or consent of department. Eigenvalue
problems; numerical Fourier transforms; modeling of data;
introduction to numerical solution of initial and boundary value
problems in ordinary and partial differential equations.
MATH 4252G Numerical Analysis
3 cr.
Prerequisites: MATH 2221 and 4251, or consent of department. Eigenvalue
problems; numerical Fourier transforms; modeling of data;
introduction to numerical solution of initial and boundary value
problems in ordinary and partial differential equations.
MATH 4270 Intro to Optimization
3 cr.
Prerequisites: MATH 2115 and 2511 or consent of department. Methods
for optimization of physical, economic, and business systems. Convex
sets; methods for solving linear programming problems; review
of classical methods of optimization; network flow analysis.
MATH 4270G Intro to Optimization
3 cr.
Prerequisites: MATH 2115 and 2511 or consent of department. Methods
for optimization of physical, economic, and business systems. Convex
sets; methods for solving linear programming problems; review
of classical methods of optimization; network flow analysis.
MATH 4280 Math Modeling Continuous Systm
3 cr.
Prerequisite: MATH 2115 and 2221, or consent of department. General
principles in mathematical modeling, derivation and analysis of
specific models using ordinary and partial differential equations;
examples drawn from the applied sciences may include traffic
flow, biological systems, mechanical systems, discussion of stability
and dependence on parameters.
MATH 4280G Math Modeling Continuous Systm
3 cr.
Prerequisite: MATH 2115 and 2221, or consent of department. General
principles in mathematical modeling, derivation and analysis of
specific models using ordinary and partial differential equations;
examples drawn from the applied sciences may include traffic
flow, biological systems, mechanical systems, discussion of stability
and dependence on parameters.
MATH 4301 Analysis Variance & Exp Design
3 cr.
Prerequisite: MATH 2314 or other introductory level statistics course,
or consent of department. Only one of MATH 4301 or MATH 6301 may
be counted toward a master’s degree in Mathematics. An introduction
to the SAS statistical computer package. Basic analysis of variance
with fixed and random effects models, multifactor analysis
of variance, analysis of covariance. Experimental designs including
completely randomized designs, randomized block designs, nested
designs, and Latin squares.
MATH 4301G Analysis Variance & Exp Design
3 cr.
Prerequisite: MATH 2314 or other introductory level statistics course,
or consent of department. Only one of MATH 4301 or MATH 6301 may
be counted toward a master’s degree in Mathematics. An introduction
to the SAS statistical computer package. Basic analysis of variance
with fixed and random effects models, multifactor analysis
of variance, analysis of covariance. Experimental designs including
completely randomized designs, randomized block designs, nested
designs, and Latin squares.
MATH 4304 Intro to Regression Analysis
3 cr.
Prerequisite: MATH 2314 or other introductory level statistics course,
or consent of department. Only one of MATH 4304 or 6304 may be
counted toward a master’s degree in Mathematics. Linear regression,
inferences in regression analysis, aptness of model and remedial
measures, matrices, multiple and polynomial regression, indicator
variables, multi-collinearity, selection of independent variables,
nonlinear regression. SAS will be used for data analysis.
MATH 4304G Intro to Regression Analysis
3 cr.
Prerequisite: MATH 2314 or other introductory level statistics course,
or consent of department. Only one of MATH 4304 or 6304 may be
counted toward a master’s degree in Mathematics. Linear regression,
inferences in regression analysis, aptness of model and remedial
measures, matrices, multiple and polynomial regression, indicator
variables, multi-collinearity, selection of independent variables,
nonlinear regression. SAS will be used for data analysis.
MATH 4310 Matrix Theory for Statistics
3 cr.
Prerequisite: MATH 2511 or the consent of the department. Emphasis
is on topics in matrix theory which frequently arise in the study of
statistics. Topics in include eigenvalues and eigenvectors, generalized
inverses, matrix decomposition, linear systems, matrix derivatives,
and special matrices. Topics in statistics are not a portion of
this course.
MATH 4310G Matrix Theory for Statistics
3 cr.
Prerequisite: MATH 2511 or the consent of the department. Emphasis
is on topics in matrix theory which frequently arise in the study of
statistics. Topics in include eigenvalues and eigenvectors, generalized
inverses, matrix decomposition, linear systems, matrix derivatives,
and special matrices. Topics in statistics are not a portion of
this course.
University of New Orleans/301