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Course Criteria
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3.00 Credits
Concentrated study in a specific area or areas of application, with an emphasis on modeling and visualization. Areas may include computational biology, computational chemistry, computational applied mathematics, computational economics, computational physics, or computational geology. Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Varies with the topic and is given in the Course Schedule.
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3.00 Credits
Study of simple and multiple regression, fundamentals of experimental design, and analysis of variance methods. May include logistic regression, Poisson regression, resampling methods, introduction to Bayesian methods, and probability models. Includes substantial use of statistical software. Three lecture hours and one laboratory hour a week for one semester. Prerequisite: Mathematics 316, Statistics and Scientific Computation 303, 304, 305, or 306.
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3.00 Credits
Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Upper-division standing. Additional prerequisites may vary with the topic and are given in the Course Schedule.
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3.00 Credits
Basic concepts of discrete-event simulation. Statistical input and output analysis; application of simulation software; modeling of systems under uncertainty. Three lecture hours a week for one semester. Statistics and Scientific Computation 358 (Topic: Simulation Modeling) and 367S may not both be counted. Prerequisite: Upper-division standing; Statistics and Scientific Computation 321 or an equivalent introductory statistics course, with a grade of at least C-; and Mathematics 408C or 408K, with a grade of at least C-.
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3.00 Credits
Study of parallel computing principles, architectures, and technologies; and parallel application development, performance, and scalability. Designed to help prepare students to formulate and develop parallel algorithms to implement effective applications for parallel computing systems. Three lecture hours a week for one semester. Prerequisite: Mathematics 408D or 408M; Mathematics 340L; and prior programming experience using C or Fortran on Linux or Unix systems.
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3.00 Credits
Distributed and grid computing principles and technologies. Covers common modes of grid computing for scientific applications, development of grid-enabled applications, and future trends in grid computing. Three lecture hours a week for one semester. Prerequisite: Mathematics 408D or 408M; Mathematics 340L; and prior programming experience using C or Fortran on Linux or Unix systems.
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3.00 Credits
Scientific visualization principles, practices, and technologies, including remote and collaborative visualization. Introduces statistical analysis, data mining, and feature detection. Three lecture hours a week for one semester. Prerequisite: Mathematics 408D or 408M; Mathematics 340L; and prior programming experience using C or Fortran on Linux or Unix systems.
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3.00 Credits
Three lecture hours a week for one semester. May be repeated for credit when the topics vary. Prerequisite: Upper-division standing. Additional prerequisites may vary with the topic and are given in the Course Schedule.
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3.00 Credits
Same as Mathematics 378K. Sampling distributions of statistics, estimation of parameters (confidence intervals, method of moments, maximum likelihood, comparison of estimators using mean square error and efficiency, sufficient statistics), hypothesis tests (p-values, power, likelihood ratio tests), and other topics. Three lecture hours a week for one semester. Prerequisite: Mathematics 362K with a grade of at least C-.
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3.00 Credits
This course is used to record credit the student earns while enrolled at another institution in a program administered by the University's Study Abroad Office or the school's BBA Exchange Programs. Credit is recorded as assigned by the study abroad adviser in the Department of Information, Risk, and Operations Management. University credit is awarded for work in an exchange program; it may be counted as coursework taken in residence. May be repeated for credit when the topics vary.
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