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[[Lecture30_blog_ECE302S13_Boutin|30]])
 
[[Lecture30_blog_ECE302S13_Boutin|30]])
 
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In Lecture 24,  
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In Lecture 24, we talked about the expectation of a 2D random variable, and more generally the expectation of any function of a 2D random variable. In particular, we looked at the covariance of two variables.  We finished the lecture by giving the definition of conditional probability density function and illustrating it with an example.
  
  
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*Read Sections 5.5, 5.6, 5.7 in the textbook
 
*Read Sections 5.5, 5.6, 5.7 in the textbook
 
*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.)
 
*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.)
::Compute the probability that a meeting will occur
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::[[Practice_Question_probability_meeting_occurs_ECE302S13Boutin|Compute the probability that a meeting will occur]]
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::[[Practice_Question_find_conditional_pdf_ECE302S13Boutin|find the conditional probability density function]]
  
Previous: [[Lecture22_blog_ECE302S13_Boutin|Lecture 23]]
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Previous: [[Lecture23_blog_ECE302S13_Boutin|Lecture 23]]
  
Next: [[Lecture24_blog_ECE302S13_Boutin|Lecture 25]]
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Next: [[Lecture25_blog_ECE302S13_Boutin|Lecture 25]]
 
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[[2013_Spring_ECE_302_Boutin|Back to 2013 Spring ECE302 Boutin]]
 
[[2013_Spring_ECE_302_Boutin|Back to 2013 Spring ECE302 Boutin]]

Latest revision as of 12:11, 5 March 2013


Lecture 24 Blog, ECE302 Spring 2013, Prof. Boutin

Monday March 4, 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 24, we talked about the expectation of a 2D random variable, and more generally the expectation of any function of a 2D random variable. In particular, we looked at the covariance of two variables. We finished the lecture by giving the definition of conditional probability density function and illustrating it with an example.


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

  • Read Sections 5.5, 5.6, 5.7 in the textbook
  • 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.)
Compute the probability that a meeting will occur
find the conditional probability density function

Previous: Lecture 23

Next: Lecture 25


Back to 2013 Spring ECE302 Boutin

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