Line 37: Line 37:
  
  
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
Line 47: Line 57:
 
----
 
----
 
==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

Back to ECE302 Spring 2013 Prof. Boutin

Alumni Liaison

Basic linear algebra uncovers and clarifies very important geometry and algebra.

Dr. Paul Garrett