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#1
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I could not use Bayes' theorem to solve Problem 1.1 but I thought of an 'alternative' method which gave me the answer 2/3. I want to know if this method is right or not. It's as follows:
Since there are 2 black balls and 1 white ball left are choosing the first black ball, the chances that the second ball is black is 2/3 since there are 3 balls left. Is this method right or not? |
#2
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For instance, if we changed the statement of the problem to having two bags one with two black balls and one with two white balls, and you picked a bag that produced a black ball, the second ball will be black with probability 100%, notwithstanding that the total remaining balls in both bags are two white and one black.
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Where everyone thinks alike, no one thinks very much |
#3
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Can you elaborate on the hint for this problem? It seems to me that in your alternative problem you aren't using Bayes' Theorem. Wouldn't using Bays' dictate that you would say P[A|B] stands for the probability that the second ball is black assuming that the first ball is black, which in your problem would be 100% and P[B] stands for the probability that the first ball is black, which would be 50% because either the bag with two white balls or the bag with two black balls could be chosen. Therefore P[A|B]P[B] = 1/2.
I understand your result intuitively. I just don't understand how Bayes' Theorem is being applied to arrive at that result as direction by the hint in the textbook. |
#4
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In the original problem, the conditional probability is not as straightforward to compute as in the simplified case here. One way to use Bayes' theorem in the original problem is to determine the joint P(A,B) for all combinations of A and B, and from that you can calculate all other probabilities including the conditional probability.
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Where everyone thinks alike, no one thinks very much |
#5
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Hi professor, with your example -- having two bags one with two black balls and one with two white balls.
I thought we had: P[first ball is black] = P[B] = 1/2 P[first ball is black and second ball is back] = P[A and B] = 1/2 P[second ball is black given first ball is back] = P[A | B] = P[A and B] / P[B] (by Bayes' Theorem) = 1/2 / 1/2 = 1 eshmrt said "P[A|B]P[B] = 1/2" and you said the calculation is right...so I am confused. Maybe I miss something... |
#6
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Where everyone thinks alike, no one thinks very much |
#7
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Argh, sorry, my bad. misread the symbol.
Thanks for confirming ![]() |
#8
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No worries. Happens in the best families.
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Where everyone thinks alike, no one thinks very much |
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