|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
3.00 Credits
Fundamentals of set operations, maps and relations, groups, rings and field theory. Topics include permutation groups, cosets, homomorphisms and isomorphisms, direct product of groups and rings, integral domains field of quotients, fundamental properties of integers, the ring of integers modulo n, and rings of polynomials. Applications.
-
0.00 - 3.00 Credits
Fundamentals of set operations, maps and relations, groups, rings and field theory. Topics include permutation groups, cosets, homomorphisms and isomorphisms, direct product of groups and rings, integral domains field of quotients, fundamental properties of integers, the ring of integers modulo n, and rings of polynomials. Applications. Prerequisites: MATH 3311 and MATH 3313. Spring.
-
3.00 Credits
An introduction to partial differential equations emphasizing the wave, diffusion and potential (Laplace) equations. A focus on understanding the physical meaning and mathematical properties of solutions of partial differential equations. Methods include fundamental solutions and transform methods for problems on the line, and separation of variables using orthogonal series for problems in regions with boundary. Additional topics include higher dimensional problems and special topics like Harmonic functions, the maximum principle, Green’s functions etc.
-
0.00 - 3.00 Credits
An introduction to partial differential equations emphasizing the wave, diffusion and potential (Laplace) equations. A focus on understanding the physical meaning and mathematical properties of solutions of partial differential equations. Methods include fundamental solutions and transform methods for problems on the line, and separation of variables using orthogonal series for problems in regions with boundary. Additional topics include higher dimensional problems and special topics like Harmonic functions, the maximum principle, Green's functions etc. (May be taken for graduate credit.) Prerequisites: MATH 3315 and MATH 3470. Offered Spring of odd years.
-
3.00 Credits
Introduction to the formulation of linear models and the estimation of the parameters of such models, with primary emphasis on least squares. Application of multiple regression and curve fitting and the design of experiments for fitting regression models.
-
2.00 Credits
Introduction to the formulation of linear models and the estimation of the parameters of such models, with primary emphasis on least squares. Application of multiple regression and curve fitting and the design of experiments for fitting regression models. (May be taken for graduate credit.) Prerequisites: MATH 1342 or MATH 2342 or the equivalent, or MATH 1470. Offered on sufficient demand.
-
3.00 Credits
A continued study of topics from Discrete Mathematics I with additional topics from discrete mathematics that have strong application to the field of computer science. Additional topics include: recurrence relations, formal languages, and finite-state machines.
-
0.00 - 3.00 Credits
A continued study of topics from Discrete Mathematics I with additional topics from discrete mathematics that have strong application to the field of computer science. Additional topics include: recurrence relations, formal languages, and finite-state machines. Prerequisites: MATH 2305, COSC 2437. Spring.
-
3.00 Credits
A first course in mathematical statistics and is taught from a classical viewpoint. Topics include: Set theory, counting techniques, probability axioms, probability density and distribution functions, common distributions, mathematical expectations, functions of random variables, sampling distributions, estimation, hypothesis testing including the likelihood ratio test and the Neyman Pearson theory, regression and correlation. Prerequisite: MATH 3470 required, MATH 3342 recommended. Spring of odd years.
-
0.00 - 3.00 Credits
A first course in mathematical statistics and is taught from a classical viewpoint. Topics include: Set theory, counting techniques, probability axioms, probability density and distribution functions, common distributions, mathematical expectations, functions of random variables, sampling distributions, estimation, hypothesis testing including the likelihood ratio test and the Neyman Pearson theory, regression and correlation. (May be taken for graduate credit.) Prerequisite: Math 3470, Math 3342 is recommended. Spring.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2025 AcademyOne, Inc.
|
|
|