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[[Lecture30_blog_ECE302S13_Boutin|30]])
 
[[Lecture30_blog_ECE302S13_Boutin|30]])
 
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In Lecture 26,  
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In Lecture 26, we defined independence for continuous random variables, and we justified the definition by showing that it is equivalent to the definition we used in the context of set-theoretic probability theory. We then covered the topic of "functions of a random variable". More specifically, we explained and illustrated a two step procedure to find the pdf of a random variable Y defined as a function Y=g(X) of another random variable X.
  
  
 
==Action items for students (to be completed before next lecture)==
 
==Action items for students (to be completed before next lecture)==
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*Solve the following practice problem and consider sharing your solution for discussion and feedback. (You will hand in your solution later as part of homework 6.)
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**[[Practice_Question_independence_ECE302S13Boutin|Determine if X and Y independent from their joint density]]
  
 
Previous: [[Lecture25_blog_ECE302S13_Boutin|Lecture 25]]
 
Previous: [[Lecture25_blog_ECE302S13_Boutin|Lecture 25]]

Revision as of 04:47, 9 March 2013


Lecture 26 Blog, ECE302 Spring 2013, Prof. Boutin

Friday March 8, 2013 (Week 9) - See Course Outline.

(Other blogs 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)


In Lecture 26, we defined independence for continuous random variables, and we justified the definition by showing that it is equivalent to the definition we used in the context of set-theoretic probability theory. We then covered the topic of "functions of a random variable". More specifically, we explained and illustrated a two step procedure to find the pdf of a random variable Y defined as a function Y=g(X) of another random variable X.


Action items for students (to be completed before next lecture)

Previous: Lecture 25

Next: Lecture 27


Back to 2013 Spring ECE302 Boutin

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