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Wednesday January 30, 2013 (Week 4) - See [[LectureScheduleECE302Spring13_Boutin|Course Outline]]. | Wednesday January 30, 2013 (Week 4) - See [[LectureScheduleECE302Spring13_Boutin|Course Outline]]. | ||
− | ( | + | (Jump to Lecture [[Lecture1_blog_ECE302S13_Boutin|1]], |
[[Lecture2_blog_ECE302S13_Boutin|2]], | [[Lecture2_blog_ECE302S13_Boutin|2]], | ||
[[Lecture3_blog_ECE302S13_Boutin|3]], | [[Lecture3_blog_ECE302S13_Boutin|3]], | ||
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[[Lecture30_blog_ECE302S13_Boutin|30]]) | [[Lecture30_blog_ECE302S13_Boutin|30]]) | ||
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− | In Lecture 10, ... | + | ==Lecture Summary== |
− | + | In Lecture 10, defined the concept of a discrete random variables and gave several examples. The concept that caused the most confusion seems to be the probability mass function, for which the argument must be a number (or vector of numbers). This is in contrast with the probability law P, whose argument is a set. | |
+ | ---- | ||
==Action items for students (to be completed before next lecture)== | ==Action items for students (to be completed before next lecture)== | ||
+ | *Read Section 3.1 in the textbook. | ||
+ | |||
+ | ---- | ||
+ | ==Comments/discussions== | ||
+ | *Add a comment/quetion here. | ||
+ | *Add a comment/quetion here. | ||
+ | ---- | ||
+ | ==Navigation== | ||
+ | Previous Blog: [[Lecture9_blog_ECE302S13_Boutin|Lecture 9]] | ||
− | + | Next Blog: [[Lecture11_blog_ECE302S13_Boutin|Lecture 11]] | |
− | + | [[2013_Spring_ECE_302_Boutin|Back to course wiki]] | |
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Latest revision as of 10:08, 30 January 2013
Contents
Lecture 10 Blog, ECE302 Spring 2013, Prof. Boutin
Wednesday January 30, 2013 (Week 4) - See Course Outline.
(Jump to Lecture 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)
Lecture Summary
In Lecture 10, defined the concept of a discrete random variables and gave several examples. The concept that caused the most confusion seems to be the probability mass function, for which the argument must be a number (or vector of numbers). This is in contrast with the probability law P, whose argument is a set.
Action items for students (to be completed before next lecture)
- Read Section 3.1 in the textbook.
Comments/discussions
- Add a comment/quetion here.
- Add a comment/quetion here.
Previous Blog: Lecture 9
Next Blog: Lecture 11