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MATH 510 - Mathematcl/Statistcl Computing |

The goal of this course is to provide students with programming background sufficient for graduate level study in mathematics and statistics. The course gives an introduction to R, SAS, Python and cloud computing. R and SAS are the statistical packages most widely used by practicing statisticians. This portion of the course will be structured around statistical methods and examples will be worked out using both computing environments. Statistical topics to be covered include data management, simulation, descriptive statistics, graphical displays, hypothesis testing, correlation, regression models, and simple multivariate analysis methods. The introduction to Python will cover the basic structure of the language, commands, scripts and graphing. The big data and cloud computing portion will focus on data sets that are too large to be analyzed on a conventional personal computer, obtaining and managing an account in a cloud server and learning basic elements of Apache Hadoop software for distributed storage and computing Text material will be announced and available online without cost. Fall and Spring each year. Restrictions: Must be enrolled in one of the following Levels: MN or MC Graduate Must be enrolled in one of the following Majors: Mathematics and Statistics 3.000 Credit hours 3.000 Lecture hours 0.000 Lab hours Levels: MN or MC Graduate, Undergraduate Schedule Types: Lecture Mathematics Department Restrictions: Must be enrolled in one of the following Levels: MN or MC Graduate Must be enrolled in one of the following Majors: Mathematics and Statistics |

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