{"id":4010,"date":"2017-12-13T16:01:24","date_gmt":"2017-12-13T22:01:24","guid":{"rendered":"http:\/\/www.comm.utoronto.ca\/dkundur\/?page_id=4010"},"modified":"2024-07-16T17:50:51","modified_gmt":"2024-07-16T23:50:51","slug":"ece-286-probability-and-statistics","status":"publish","type":"page","link":"https:\/\/www.comm.utoronto.ca\/dkundur\/course\/ece-286-probability-and-statistics\/","title":{"rendered":"ECE 286: Probability and Statistics"},"content":{"rendered":"

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A course in probability and statistics for Engineering Science students focusing on building solid probabilistic and statistical foundations. Topics include: sample space, events, definitions of probability, conditional probability, Bayes’ theorem, important classes of discrete and continuous random variables and their distributions, joint, conditional, and marginal distributions, expectation, moment generating and characteristic functions, transformations of random variables, central limit theorem and approximations. Graphical methods, quantile plots, point and interval estimation of population parameters, method of maximum likelihood. Hypotheses testing, simple and multiple regression, correlation analysis, and introduction to Bayesian statistics.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Course Team<\/h3>\n\n\n\n
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Instructor<\/h4>\n
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  • Professor Deepa Kundur<\/li>\n<\/ul>\n

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Course Syllabus<\/h3>\n

This course makes use of the following text:<\/p>\n

R.E. Walpole, R.H. Myers, S.L. Myers and K. Ye, Probability & Statistics for Engineers\u00a0<\/i>& Scientists<\/i>, 9th<\/sup> ed., Pearson, Inc., 2011. ISBN-13 978-0-13-411585-6.<\/p>\n

The following topics and text book sections are covered in this course:<\/p>\n