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MATH 501 - Probability Theory/Application |

Probability Theory and Applications. This is a graduate level introduction to probability theory. Topics include probability measures, independence and conditional probability, discrete and continuous random variables and their properties, joint distributions, moment generating functions, elements of Poisson processes, notions of convergence, Laws of Large Numbers, and the Central Limit Theorem. A working knowledge of multiple integrals and partial derivatives is essential for this course. Some previous exposure to elementary probability and statistics, at least at the level of Math 040, is recommended. This course is not based on measure theory. Textbook: A Course in Probability, Neil A. Weiss (Addison Wesley, 2005) Prerequisites: Math 137, Math 150 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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