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IT 962: Advanced Topics in Computer Security
3.00 Credits
George Mason University
Credits: 3 Current topics of advanced research. Content varies depending on faculty interests, research developments, and student demand. Requires substantial student participation. May include formal models for computer security, multilevel data models, multilevel database management system architectures, secure concurrency control protocols, distributed secure system architectures, integrity models and mechanisms, security policy, and requirements analysis. Prerequisites IT 862 or 865, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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IT 962 - Advanced Topics in Computer Security
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IT 971: Probability Theory
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with STAT 971 A rigorous measure-theoretic treatment of probability. Includes expectation, distributions, laws of large numbers and central limit theorems for independent random variables, characteristic function methods, conditional expectations, martingales, strong and weak convergence, and Markov chains. Prerequisites STAT 544 and MATH 315. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered AS
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IT 971 - Probability Theory
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IT 972: Mathematical Statistics I
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with STAT 972/CSI 972 Focuses on theory of estimation. Includes method of moments, least squares, maximum likelihood, and maximum entropy methods. Details methods of minimum variance unbiased estimation. Topics include sufficiency and completeness of statistics, Fisher information, Cramer-Rao bounds, Bhattacharyya bounds, asymptotic consistency and distributions, statistical decision theory, minimax and Bayesian decision rules, and applications to engineering and scientific problems. Prerequisites STAT 652/CSI 672 or equivalent, and either IT 876/STAT 876/CSI 876 or IT 971/STAT 971. Hours of Lecture or Seminar per week 3 When Offered AF
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IT 972 - Mathematical Statistics I
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IT 973: Mathematical Statistics II
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with STAT 973/CSI 973 Continuation of IT 972/STAT 972/CSI 972. Concentrates on theory of hypothesis testing. Topics include characterizing decision process, simple versus complex hypothesis tests, Neyman-Pearson Lemma, uniformly most powerful tests, unbiasedness and invariance of tests, and randomized and sequential tests.Applications of testing principles made to situations in normal distribution family and other families of distributions. Prerequisites IT 972/STAT 972/CSI 972 Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered AS
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IT 973 - Mathematical Statistics II
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IT 976: Statistical Inference for Stochastic Processes
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with CSI 976 Modern theory of parameter estimation and hypothesis testing for stochastic processes, counting processes with random intensities, and solutions to stochastic differential equations driven by martingales. Considers applications to engineering, biology, and economics. Prerequisites IT 746/CSI 776 Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered AS
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IT 976 - Statistical Inference for Stochastic Processes
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IT 978: Statistical Analysis of Signals
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with CSI 978 Advanced course in analysis of discrete- and continuous-time signals using methods of stochastic differential equations and time series. Presumes familiarity with methods of harmonic analysis and times series modeling. Topics include statespace modeling and eigen-value processing, nonlinear modeling of signals, non-Gaussian stochastic process structure, detection and estimation of vector-valued signals, robust signal detection, with applications to array processing and target tracking. Prerequisites STAT 544 and 658, or equivalent. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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IT 978 - Statistical Analysis of Signals
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IT 979: Topics in Statistical Aspects of Information Technology
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with CSI 979 Studies statistical science and body of methods and techniques that convert raw data into information. Topics include high-interaction statistical graphics, stochastic methods for parallel computing, cryptography and covert communications, order-restricted inference, treatments of imprecision, and foundations of inference. Prerequisites STAT 652 or equivalent. Notes Contents vary. May be repeated when topics distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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IT 979 - Topics in Statistical Aspects of Information Technology
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IT 980: Advanced Topics in Applied Probability
3.00 Credits
George Mason University
Credits: 3 Special topics and recent developments in field of applied probability. May include computational probability, stochastic point processes, advanced queuing theory, traffic and transportation models, percolation, processes of random aggregation and coagulation, and Markov decision processes. Prerequisites OR 645 and 647, or permission of instructor depending on semester topics. Notes May be repeated for credit when topics distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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IT 980 - Advanced Topics in Applied Probability
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IT 981: Advanced Topics in Optimization
3.00 Credits
George Mason University
Credits: 3 Special topics and recent developments. Contents vary and may include topics in linear, nonlinear, combinatorial, network, global, or stochastic optimization. Prepares students to perform research in optimization, and requires active student participation. Prerequisites IT 741, 750, 881, 882, or 884 Notes May be repeated for credit when topics distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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IT 981 - Advanced Topics in Optimization
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IT 990: Dissertation Topic Presentation
1.00 Credits
George Mason University
Credits: 1 Cross-Listed with CS 990 Students put together a professional presentation of a research proposal and present it for critique to fellow students and interested faculty. May be repeated with change of research topic, but credit toward doctoral degree is given once. Prerequisites Completion of all course requirements for PhD, or permission of instructor. Notes May be repeated with change in topic, but degree credit is given only once. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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IT 990 - Dissertation Topic Presentation
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