Statistics with Baye's theorem and partitions

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SUMMARY

This discussion focuses on applying Bayes' theorem and understanding probability distributions in the context of specific questions related to independent events. The participants clarify the conditions under which three events are independent, specifically stating that for events A, B, and C, the relationship p(A and B and C) = p(A)p(B)p(C) must hold. Additionally, they emphasize the importance of ensuring that the sum of probabilities Σall x P(X=x | Y=2) equals one when constructing distribution tables. The conversation highlights the necessity of correctly identifying probabilities for events to maintain valid distributions.

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  • Understanding of Bayes' theorem
  • Knowledge of probability distributions
  • Familiarity with independent events in probability
  • Ability to construct and interpret distribution tables
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  • Explore the concept of independence in probability with multiple events
  • Practice constructing distribution tables for various conditions
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Students and professionals in statistics, data science, and mathematics who seek to deepen their understanding of probability theory and its applications, particularly in relation to Bayes' theorem and event independence.

rock.freak667
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Well the questions and solutions are in one for some and I will type out the rest.

Q6
http://img249.imageshack.us/img249/2757/47026197.jpg

Q4
http://img237.imageshack.us/img237/1802/93774799.jpg
Q3
http://img3.imageshack.us/img3/5919/34981698.jpg

Q1
http://img19.imageshack.us/img19/7307/25729239.jpg

I need some help doing Q3 and I need some clarification with Q1.

With Q1, if Y=2, then there are only two possibilities, (1,2) and (1,2). So X can only be equal to 3 thus I am not sure how to write out the distribution table.http://img222.imageshack.us/img222/9981/95680883.jpg
 
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for Q1, there's no reason not to include (2,2) as well (twice)

for Q3, three events would be independent if p(A and B and C) = p(A)p(B)p(C), and the three possible pairs are independent (e.g A and C), just a natural extension from two events
 
Mulder said:
for Q1, there's no reason not to include (2,2) as well (twice)
Right, but wouldn't then my distribution not all add up to one either way? Σall x P(X=x)≠1

Mulder said:
for Q3, three events would be independent if p(A and B and C) = p(A)p(B)p(C), and the three possible pairs are independent (e.g A and C), just a natural extension from two events

This I know, but I don't know what numbers I'd write down for P(A) and so on.
 
rock.freak667 said:
Right, but wouldn't then my distribution not all add up to one either way? Σall x P(X=x)≠1


You should just have Σall x P(X=x | Y=2) =1



This I know, but I don't know what numbers I'd write down for P(A) and so on.


I drew the square with corners at 0, (0,1), (1,1), (1,0) ao P(A) = P(B) =1/2 etc.
 

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