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This is a great slecture, and the information given below is nitpicking, in case you want to make your video lectures even *more* awesome.
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In general, the pace of the slides is slightly too quick, but okay. You know the topic better than the person watching! There is one exception: some of the early slides flick past too quickly to read. I suppose an interested student could pause the slides to look at the formula, but then you're not explaining what is happening in some of these slides.
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Also, when you introduce the Law of Total Probability you fail to mention it by name. That would have been a useful referent for a student new to the topic.
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At 4:41 minutes, you introduce the expression X = Zk, but it is not clear that the "k" is a subscript. It would be helpful to explicitly link Zk back to the discussion on Total Probability, and that Zk is a set in a partition of Omega. Remember, you are far more familiar with the format of your slides than someone watching it.
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Overall, however, the slecture is excellent, and an interested student could simply rewind and rewatch to pick up on the details. Good job!
  
 
This slecture will be reviewed by AM
 
This slecture will be reviewed by AM

Revision as of 16:12, 1 May 2014

Questions and Comments for: Derivation of Bayes' Rule

A slecture by Jieun Kim


Please leave me comment below if you have any questions, if you notice any errors or if you would like to discuss a topic further.


  • Questions and Comments



Back to Derivation of Bayes' Rule


This is a great slecture, and the information given below is nitpicking, in case you want to make your video lectures even *more* awesome.

In general, the pace of the slides is slightly too quick, but okay. You know the topic better than the person watching! There is one exception: some of the early slides flick past too quickly to read. I suppose an interested student could pause the slides to look at the formula, but then you're not explaining what is happening in some of these slides.

Also, when you introduce the Law of Total Probability you fail to mention it by name. That would have been a useful referent for a student new to the topic.

At 4:41 minutes, you introduce the expression X = Zk, but it is not clear that the "k" is a subscript. It would be helpful to explicitly link Zk back to the discussion on Total Probability, and that Zk is a set in a partition of Omega. Remember, you are far more familiar with the format of your slides than someone watching it.

Overall, however, the slecture is excellent, and an interested student could simply rewind and rewatch to pick up on the details. Good job!

This slecture will be reviewed by AM

Alumni Liaison

Questions/answers with a recent ECE grad

Ryne Rayburn