|
|
|
|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
4.00 Credits
This is a continuation of 1016-451 covering classical and Bayesian methods in estimation theory; chi-square test; Neyman-Pearson lemma; mathematical justifi cation of standard test procedures; suffi cient statistics and further topics in statistical inference. (1016-451) Class 4, Credit 4 (S)
-
4.00 Credits
This is an in-depth study of inferential procedures that are valid under a wide range of shapes for the population distribution. Topics include tests based on the binomial distribution, contingency tables, statistical inferences based on ranks, runs tests and randomization methods. A statistical software package is used for data analysis. (1016-314 or 1016-352) Class 4, Credit 4 (F)
-
4.00 Credits
This course provides a basis for understanding the selection of the appropriate tools and techniques for analyzing survey data. Topics include design of sample surveys, methods of data collection, a study of standard sampling methods. A statistical software package is used for data analysis. (1016-352 or 1016-314) Class 4, Credit 4 (S)
-
4.00 Credits
This course explores problem solving, formulation of the mathematical model from physical considerations, solution of the mathematical problem, testing the model, and interpretation of results. Problems are selected from the physical sciences, engineering and economics. (1016-305, 306, 331, 352) Class 4, Credit 4 (F, W)
-
4.00 Credits
This course is a presentation of the general linear programming problem. A review of pertinent matrix theory, convex sets and systems of linear inequalities; the simplex method of solution; artifi cial bases; duality; parametric programming; and applications are covered. (1016-331) Class 4, Credit 4 ( offered upon suffi cient request)
-
4.00 Credits
This course provides a study of the theory of optimization of linear and nonlinear functions of several variables with or without constraints. Applications of this theory to solve problems in business, management, engineering, and the sciences are considered. Algorithms for practical applications will be analyzed and implemented. Students taking this course will be expected to complete applied projects and/or case studies. (1016-465 or equivalent) Class 4, Credit 4 (offered upon suffi cient request)
-
4.00 Credits
The basic theory of graphs and networks, including the concepts of circuits, trees, edge and vertex separability, planarity and vertex coloring, and partitioning are discussed. There is a strong emphasis on applications to physical problems and on graph algorithms such as those for spanning trees, shortest paths, non-separable blocks and network fl ows. (1016-265) Class 4, Credit 4 (F, S)
-
4.00 Credits
This is an introduction to computer simulation, simulation languages, model building and computer implementation, and mathematical analyses of simulation models and their results using techniques from probability and statistics. (1016-352, 4003-231, 232 or permission of the instructor) Class 4, Credit 4 (offered upon suffi cient request)
-
3.00 Credits
The students work on a research topic under the supervision of a faculty member. A form describing the research goals must be signed by the faculty member and the head of the school before registration. (Permission of instructor) Credit 2-4 (F, W, S, SU)
-
2.00 Credits
This course helps students develop strategies for solving problems that are chosen from a wide variety of areas in mathematics. Emphasis is on attempting problem solutions and presentation of efforts to the class or to the instructor. (One year of calculus or permission of instructor) Class 2, Credit 2 (F)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2024 AcademyOne, Inc.
|
|
|