Syllabus_36-217_Fall10

Syllabus_36-217_Fall10 - Instructor: Alessandro Rinaldo...

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Instructor: Alessandro Rinaldo Offi ce:Baker Hall 229I Email: arinaldo@stat.cmu.edu Offi ce Hours:Wednesday, noon - 1:00pm, Baker Hall 229I Daniel Park. Offi ce Hours: Tuesday, 2:00pm-3:00pm, FMS 320. Zhanwu Liu. Offi ce Hours: Wednesday, 2:00pm-5:00pm, FMS 320. Introduction to Probability, by D.P. Bertsekas and J.N. Tsitsiklis, Athena Scientifc, 2008 (2 nd edition) Tuesday and Thursday, 10:30am - 11:50am, PH100. due by 4:00pm on Thursday in BH132, unless otherwise instructed. September, 28 and November, 2. TBA. Class is cancelled on August, 31. 21-118 or 21-122 or 21-123 or 21-256 or equivalent course. Basic rules o± integration in 2 dimensions. Not open to students who have received credit ±or 36-225 or 36-625. Teaching Assistants: Textbook: Class Meetings: Weekly assignments: Midterm Exams: Final Exam: Special date: Prerequisites: Course Description The theory o± probability and random processes provides the mathematical tools and ±ormalism needed to model uncertainty in virtually all scientifc areas. Nowadays, probabilistic models and statistical theory are essential ±or the development and analysis o± innumerable applications, rang- ing ±rom the analysis o± network dynamics o± circuit ±ailure rates, the development o± algorithms ±or computer vision or machine learning, image processing, cryptography, system per±ormance as- sessment, business inventory, marketing, fnance, medicine, etc. This is a frst curse in probability theory that is designed to prepare you to develop basic probabilistic models ±or describing and studying uncertain or random phenomena and to make better predictions and decisions. By the end o± this curse, students should 1. possess an adequate background and understanding o± basic concepts in probability theory; 1
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3. be proFcient in the calculus-based mathematical skills and tools needed to solve problems on basic topics in probability theory. Course objectives 1. Basic Probability. • Describe the sample space of an experiment using set notation. • ±ind the probabilities of complements, unions, and intersections of events. • Use counting tools to enumerate the number of equally likely outcomes of simple exper- iments. • Use the law of total probability and Bayes’ Rule to calculate probabilities. • DeFne and identify independence of events. • Calculate conditional probabilities of events. 2. Random Variables.
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Syllabus_36-217_Fall10 - Instructor: Alessandro Rinaldo...

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