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In Lecture 18,  
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In Lecture 18, the graded test was handed out and we went over its solution. We then continued discussing continuous random variables. In particular, we noted how the meaning of the pdf differs from its discrete analogue, the pmf. (The latter has the units of a probability, while the former has the units of a probability per "space" unit. ) We also looked at an example of continuous random variable, namely the exponential random variable.
 
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==Action items for students (to be completed before next lecture)==
 
==Action items for students (to be completed before next lecture)==
*Solve problems 3.88, 3.90, 3.01 in the textbook. This completes [[HW4_ECE302_S13_Boutin| homework 4]]. Please hand in all the problems for [[HW4_ECE302_S13_Boutin|homework 4]] in class on Wednesday.  
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*Solve problems 3.88, 3.90, 3.91 in the textbook. This completes [[HW4_ECE302_S13_Boutin| homework 4]]. Please hand in all the problems for [[HW4_ECE302_S13_Boutin|homework 4]] in class on Wednesday.  
 
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Previous: [[Lecture16_blog_ECE302S13_Boutin|Lecture 16]]
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::<span style="color:red">Note:  Problem 3.91 was incorrectly typed as "3.01" in an earlier version of the blog.</span>
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Previous: [[Lecture17_blog_ECE302S13_Boutin|Lecture 17]]
  
Next: [[Lecture18_blog_ECE302S13_Boutin|Lecture 18]]
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Next: [[Lecture19_blog_ECE302S13_Boutin|Lecture 19]]
 
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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 08:16, 20 February 2013


Lecture 18 Blog, ECE302 Spring 2013, Prof. Boutin

Monday February 18, 2013 (Week 7) - 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 18, the graded test was handed out and we went over its solution. We then continued discussing continuous random variables. In particular, we noted how the meaning of the pdf differs from its discrete analogue, the pmf. (The latter has the units of a probability, while the former has the units of a probability per "space" unit. ) We also looked at an example of continuous random variable, namely the exponential random variable.

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

  • Solve problems 3.88, 3.90, 3.91 in the textbook. This completes homework 4. Please hand in all the problems for homework 4 in class on Wednesday.
Note: Problem 3.91 was incorrectly typed as "3.01" in an earlier version of the blog.

Previous: Lecture 17

Next: Lecture 19


Back to 2013 Spring ECE302 Boutin

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