||Applied Partial Differential Equations (4)
||A course in partial differential equations (PDEs). Topics include: mathematical models in physics, theory, and solution of quasi-linear first-order PDEs; second-order linear and nonlinear PDEs, including applications. Fourier series, boundary-value problems, Fourier and Laplace transforms. Numerical methods and solutions. Prerequisite: MATH 241 or consent of instructor.
||If you take this course you can become MATH Minor and it can be used as your Technical Elective.
||Numerical Analysis (4)
||Selected numerical and iterative processes for solving mathematical problems and their applications. Topics include finding roots with bisection and Newton’s method; solving systems of linear equations using LU decomposition and Gauss-Seidel methods; polynomial approximation using Taylor’s Theorem, Lagrange interpolations, and the theory of spline functions; numerical integration using Simpson’s rule and Gaussian integration; Prerequisite: Math 241, some programming skills
||Mathematical and Statistical Modeling (4)
||The process of expressing scientific principles, experiments, and conjectures in mathematical terms. Topics include: gathering reliable data, exposing underlying assumptions, variables, relationships, levels, refining of models, and stochastic models. Deterministic vs. stochastic, discrete vs continuous, and deductive vs statistical models. Prerequisite: Math 211
||Please see MATH Catalog
||Mathematical Statistics and Operations Research (4)
||Topics include: properties of statistics, convergence in probability, theory of estimation and confidence intervals, Bayesian statistics, tests of significance, power and uniformly most powerful tests, random processes (with emphasis on queuing theory), and stationarity. Prerequisite: Math 345
||ES 345 counts as prerequisite
||Experimental Design and Regression Analysis (4)
||Advanced course in simple and multiple linear regression analysis; nonlinear and nonparametric regression analysis. Design of experiments and analysis of variance including one-way, two-way and block design; nonparametric techniques and multiple comparison methods. Prerequisite: MATH 265 and either MATH 241 or another course in linear algebra, and MATH 345 or consent of instructor.
||Graph Theory & Combinatorics (3)
||Spring course only (generally) - Set theory, counting techniques such as permutations, combinations, generating functions, partitions and recurrence relations, Polya’s theorem, Hamiltonian and Eulerian properties of graphs, matchings, trees, coloring problems, and planarity. Applications in many disciplines. Prerequisite: MATH 142 or MATH 200 or MATH 220 or consent of instructor.
||In general Graph Theory can be very useful for the Networking class (ES 465) - NOTE Students may not earn credit for both MATH 316 and MATH 416.
||Probability Theory (4)
||Topics include probability spaces, discrete and continuous random variables, selected probability distributions for random phenomena, distributions of functions of random variables, moment generating functions, expected value, covariance and correlation, conditional expectation, law of large numbers and central limit theorem, and sampling distribution of estimators
||Allowed only if the student is graduating and cannot take equivalent ES 345
|MATH 165 (substitute for MATH 142 only)
||Elementary Applied Statistics (4)
||This course is a technology-intensive introduction to elementary statistics. Topics include: elementary descriptive and inferential statistics and their application to the behavioral, natural, and social sciences; sampling; special distributions; central limit theorem; estimation; tests of hypothesis; analysis of variance; linear regression; and correlation. Satisfies the GE Area B4 requirement for mathematics.
||You can take this course in place of MATH 142. DO NOT take MATH 131, as MATH 131 may not be very useful!
|MATH 220 (substitute for MATH 142 only)
||Reasoning and Proof (4)
||This course will teach students to analyze and evaluate scientific and rhetorical reasoning, with emphasis on the reasoning used in Mathematical proofs. Students will identify and evaluate unstated assumptions in statistical tables and charts from real-world media, submit coherent and original proofs of theorems, and develop verbal and non-verbal skills for making persuasive oral arguments and presentations on mathematical topics.
||You can take this course in place of MATH 142.MATH 220 is somewhat similar to MATH 142. DO NOT take MATH 131, as MATH 131 may not be very useful!