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SyllabusStat224 - SYLLABUS Dishwasher Safe STAT 3345Q-01:...

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SYLLABUS Dishwasher Safe STAT 3345Q-01: PROBABILITY MODELS FOR ENGINEERS Class Hour and Class Room Class Hour : Tuesdays and Thursdays 11:00am - 12:30pm every week. ( Saturday and Sunday: 4:30am-6:00am ) Class Room : CLAS 313. Website for Stat STAT 3345Q-01 P lease frequently visit the course materials website at http://www.stat.uconn.edu/ mlan for all course materials and information including course syllabus, text- books, course documents, homework assignments, final exam, and some others. The course materials will be posted also on HuskyCT. You are responsible for the material covered in the text, lectures, and homework. Instructor + Name : CYR EMILE M’LAN + Office : CLAS 324 + Office hours : Wednesday 1:00pm - 3:00pm or by appointment. ( Open on legal and illegal holidays - Closed on Sunday for mental repairs ) + Email : mlan@stat.uconn.edu + Tel : (860) 486 - 4192. + Fax : (860) 486 - 4113. 1
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About Textbooks ± Introduction to Probability and Its Applications, 3rd edition, by Richard L. Scheaffer and Linda J. Young Brooks/Cole. ISBN: 978-0-534-38671-9 ± A scientific calculator. Prerequisites P MATH 2110 or 2130 (students with solid knowledge of integral calculus) Grader Name : R. Liu Email : r.liu@uconn.edu Office : CLAS 317 Tutoring Hour at CLAS 325 (QCenter, 10hrs) Tuesday: 5:00pm-6:30pm with Yuchen Fama Thursday: 1:00pm-2:00pm with Rui Wu — 5:00pm-6:30pm Yuchen Fama Friday: 9:00am-10:00am with Yuchen Fama — 10:00am-11:00am Rui Wu — 11:00am- 12:00pm with Yuchen Fama — 5:00pm-6:30pm Rui Wu Course Description 3 Three credits. This course teaches the mathematical foundations underlying basic probability models for decision making at the intermediate level. Topics covered include: 3 Foundations of Probability: sample space and events, calculating probability of an event, counting rules, venn diagram, contingency tables . (Chapter 2) 3 Conditional Probability and Independence: calculating conditional probability, in- dependent events, multiplicative rule, law of total probability, bayes’s theorem, tree- diagram . (Chapter 3) 2
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3 Discrete Probability Distribution: discrete random variables, probability mass func- tions, expected value, variance, Tchebysheff’s rule, some common discrete probabil- ity distributions (Binomial, Geometric, Negative Binomial, Poisson, Hypergeomet-
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SyllabusStat224 - SYLLABUS Dishwasher Safe STAT 3345Q-01:...

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