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Georgetown University


Detailed Course Information


Fall 2017
Sep 28, 2022
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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)
3.000 Credit hours
3.000 Lecture hours
0.000 Lab hours

Levels: MN or MC Graduate, Undergraduate
Schedule Types: Lecture

Mathematics Department

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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