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− | Week 4-5 (Lecture [[Lecture10_blog_ECE302S13_Boutin|10]] | + | Week 4-5(6) (Lecture [[Lecture10_blog_ECE302S13_Boutin|10]],[[Lecture11_blog_ECE302S13_Boutin|11]], |
+ | [[Lecture12_blog_ECE302S13_Boutin|12]], | ||
+ | [[Lecture13_blog_ECE302S13_Boutin|13]], | ||
+ | [[Lecture14_blog_ECE302S13_Boutin|14]], | ||
+ | [[Lecture15_blog_ECE302S13_Boutin|15]], | ||
+ | [[Lecture16_blog_ECE302S13_Boutin|16]], | ||
+ | ([[Lecture17_blog_ECE302S13_Boutin|17]]) ) | ||
*2.1 Definition and examples | *2.1 Definition and examples | ||
+ | *2.2 Functions of a discrete random variable | ||
+ | *2.3 Moments of discrete random variable | ||
+ | *2.4 Conditioning of a discrete random variable | ||
+ | *2.5 Independence of discrete random variables | ||
Suggested References | Suggested References | ||
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---- | ---- | ||
==Part 3: Continuous Random Variables (To be tested in the second intra-semestrial exam)== | ==Part 3: Continuous Random Variables (To be tested in the second intra-semestrial exam)== | ||
+ | |||
+ | Week (6)7- ? (Lecture ([[Lecture17_blog_ECE302S13_Boutin|17]]) [[Lecture18_blog_ECE302S13_Boutin|18]]?) | ||
+ | *3.1 Definition of continuous random variable, probability density function. | ||
Week 6-10 (Lecture ?) | Week 6-10 (Lecture ?) |
Revision as of 10:06, 15 February 2013
ECE302 Course Outline, Spring 2013, Prof. Boutin
Part 1: Foundations (To be tested in the first intra-semestrial exam)
Week 1-3 (Lecture 1, 2, 3, 4, 5, 6, 7, 8, 9)
- 1.1 Sets
- Definition
- Operations
- De Morgan's Law
- 1.2 Probability Models
- Sample spaces
- Probability Laws (axioms, properties
- 1.3 Conditional Probabilities
- 1.4 Independence
- 1.5 Bernoulli Trials
- 1.6 Counting
Suggested references:
- Chapter 1 and 2 of the textbook,
- Chapter 1 of "Introduction to Probability," by Dimitri P. Bertsekas and John N. Tsitsiklis. Athena Scientific, Belmont, Massachusetts, 2008, ISBN 978-1-886529-23-6.
- Foundations of Probability Theory: Basic Definitions, module by Don Johnson posted on Connexions
Part 2: Discrete Random Variables (To be tested in the second intra-semestrial exam)
Week 4-5(6) (Lecture 10,11, 12, 13, 14, 15, 16, (17) )
- 2.1 Definition and examples
- 2.2 Functions of a discrete random variable
- 2.3 Moments of discrete random variable
- 2.4 Conditioning of a discrete random variable
- 2.5 Independence of discrete random variables
Suggested References
- Chapter 3 in the textbook
- Chapter 2 in "Introduction to Probability," by Dimitri P. Bertsekas and John N. Tsitsiklis. Athena Scientific, Belmont, Massachusetts, 2008, ISBN 978-1-886529-23-6.
- Chapter 4 of Collaborative Statistics by Illowski and Dean (available online)
Part 3: Continuous Random Variables (To be tested in the second intra-semestrial exam)
Week (6)7- ? (Lecture (17) 18?)
- 3.1 Definition of continuous random variable, probability density function.
Week 6-10 (Lecture ?)
Suggested References
- Chapter 4,5,6 in the textbook
Part 4: To be tested in the final exam
Week 11-15
- Stochastic Processes