Engineers often have to deal with uncertainty. When we design a bus schedule, we don't know how many people will be waiting at the stop. When we set up a computer network, we don't know which servers will experience a power failure. Probability is the mathematics that allows us to model and make decisions about scenarios that involve uncertainty. In this course we will learn about probabilistic models and how to solve them.
|Introduction. Combinatorial analysis||§1.1-1.4||ppt py|
|Axioms of probability I||§2.1-2.5||ppt py|
|Axioms of probability II||§2.5||ppt py|
|No class, spring festival|
Midterm exam 1
|Conditional probability and independence||§3.3-3.4||ppt py|
|Random variables I||§4.1-4.4||ppt py|
|Random variables II||§4.5-4.7, 4.9||ppt py|
|Continuous random variables||§5.1-5.3, 5.5||ppt py|
Midterm exam 2
|Jointly distributed random variables||§6.1-6.3||ppt|
|Properties of expectation||§7.1-7.2, 7.4, (7.5)||ppt|
|Finish limit theorems; course evaluation|
||Final exam at 9.30 in 103 John Fulton|
Homeworks will be issued on Friday every week and will be discussed in tutorials on the following Monday. Feel free to ask any questions about the homeworks there.
You will not turn in your homework solutions for grading. However some of you will be called upon to present solutions in class on Tuesday. Your solution will then be discussed among your classmates.
This presentation will count towards your grade. Students will be selected to present randomly with repetition. This means you may be called to present at any time, and more than once. It is important that you show up in class every week and that you are prepared to present solutions to (most of) the problems for that week. If you cannot make it to class on any particular week, let your TA know in advance.
You can log into the ENGG 2040C discussion forums using your campus ID and CWEM password.