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MATH 551: Linear Prog and Optimiz
3.00 Credits
College of Charleston
This course provides an introduction to deterministic models in operations research. Topics include linear programming, network analysis, dynamic programming, and game theory. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
Prerequisite:
MATH 221 AND MATH 203 AND CSCI 220
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MATH 551 - Linear Prog and Optimiz
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MATH 552: Operations Research
3.00 Credits
College of Charleston
This course provides an introduction to probabilistic models in operations research. Topics include queueing theory, applications of Markov chains, simulation, integer programming and nonlinear programming. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
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MATH 552 - Operations Research
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MATH 555: Bayesian Statistical Methods
3.00 Credits
College of Charleston
Posterior distributions using observed data are calculated and used for inferences about model parameters. Classical statistical methods are compared with the Bayesian methods and classical models such as linear regression, ANOVA, and generalized linear models are extended to include the Bayesian paradigm, Monte Carlo methods, Gibbs sampling and Metropolis-Hastings algorithms. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
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MATH 555 - Bayesian Statistical Methods
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MATH 560: Stochastic Processes
3.00 Credits
College of Charleston
Stochastic Processes are sequences of random variables indexed in either discrete or continuous time unit. They can be used to model systems that involve random elements as they evolve over time. In this course we will study Poisson processes, Markov chains, renewal processes, martingales, random walks, and Brownian motion. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
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MATH 560 - Stochastic Processes
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MATH 561: Time Series Analysis
3.00 Credits
College of Charleston
Time series are sequences of data points measured typically at successive uniform time intervals. They are used in signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, and control engineering. Time series analysis is a collection of methods for analyzing time series data in order to extract meaningful characteristics of the data. In this course we will study stationary processes, forecasting techniques, ARMA models, spectral analysis, non-stationary and seasonal models, and multivariate time series. NOTE: Please refer to the appropriate academic catalog for additional course information concerning prerequisites, co-requisites and course restrictions.
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MATH 561 - Time Series Analysis
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MATH 580: Topics In Applied Math
3.00 Credits
College of Charleston
No Description Available
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MATH 580 - Topics In Applied Math
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MATH 585: Topics In Pure Math
3.00 Credits
College of Charleston
No Description Available
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MATH 585 - Topics In Pure Math
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MATH 589: ST in Probability and Statisti
3.00 Credits
College of Charleston
No Description Available
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MATH 589 - ST in Probability and Statisti
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MATH 5MM: Math (Mat Req) 500 Lvl
3.00 Credits
College of Charleston
No Description Available
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MATH 5MM - Math (Mat Req) 500 Lvl
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MATH 601: General Topology
3.00 Credits
College of Charleston
No Description Available
Prerequisite:
MATH 311 AND MATH 411
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MATH 601 - General Topology
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