| Line 14: | Line 14: | ||
* Has anyone reserved this slecture for a review? If not, then I would like to review it -[[User:Mhossain|Maliha Hossain]] | * Has anyone reserved this slecture for a review? If not, then I would like to review it -[[User:Mhossain|Maliha Hossain]] | ||
* | * | ||
| − | * Reviewed by Yanzhe Cui: This slecture is about the concept of Bayes | + | * Reviewed by Yanzhe Cui: This slecture is about the concept of Bayes rule. The author introduced the derivation of Bayes' rule in discrete and continuous cases. Then the author gave a student attend seminar example and tried to use this example to show the advantage of using Bayes rule. The comments are: (1) please add some spaces between equation and equation number. They are confused when I first look at it; (2) what is the '''black box''' in decision tree figure (the left-most one)? if it's hard to show the conditional probability using tree format, you could choose other ways, such as just text; (3) what do you want to show in Venn diagram? Please add labels in two circles using A and B; (4) the author claim that '''<br> We can see now that <math> \textbf{ P}(A|B) > \textbf{P}(A) </math>''', what's your point? |
* | * | ||
* Additional Questions / Comments | * Additional Questions / Comments | ||
Revision as of 05:57, 7 May 2014
Questions and Comments for: Derivation of Bayes Rule
A slecture by Anonymous7
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
- Has anyone reserved this slecture for a review? If not, then I would like to review it -Maliha Hossain
- Reviewed by Yanzhe Cui: This slecture is about the concept of Bayes rule. The author introduced the derivation of Bayes' rule in discrete and continuous cases. Then the author gave a student attend seminar example and tried to use this example to show the advantage of using Bayes rule. The comments are: (1) please add some spaces between equation and equation number. They are confused when I first look at it; (2) what is the black box in decision tree figure (the left-most one)? if it's hard to show the conditional probability using tree format, you could choose other ways, such as just text; (3) what do you want to show in Venn diagram? Please add labels in two circles using A and B; (4) the author claim that
We can see now that $ \textbf{ P}(A|B) > \textbf{P}(A) $, what's your point? - Additional Questions / Comments
Back to Derivation of Bayes Rule
