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[[Lecture30_blog_ECE302S13_Boutin|30]]) | [[Lecture30_blog_ECE302S13_Boutin|30]]) | ||
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| − | In Lecture 24, | + | 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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*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 | ::Compute the probability that a meeting will occur | ||
| + | ::find the conditional probability | ||
Previous: [[Lecture22_blog_ECE302S13_Boutin|Lecture 23]] | Previous: [[Lecture22_blog_ECE302S13_Boutin|Lecture 23]] | ||
Revision as of 11:20, 4 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
Previous: Lecture 23
Next: Lecture 25
