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P(A or B)= P(A) + P(B) - P(A and B)

1) This gives an idea what is the least overlap is 1- .8 + 1- .3 =.5 which is greater than 1/3 hence this statement is sufficient.
2) P(A or B) does not tell us any thing about P(A) or P(B) insufficient.

answer is A
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Suppose A and B are two events that are not independent. Is the probability P(A and B) > 1/3?

(1) P(A) = 0.8 and P(B) = 0.7
(2) P(A or B) = 0.9


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Statement 1: We have individual probabilities for A and B, so we can obtain P(A) + P(B) - P(A and B)
Sufficient

Statement 2:
We need the individual probabilities
Insufficient

Answer: A
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When the question says "not independent", what should I do?

Should I consider that the events are NOT mutually exclusive? Is it the same? Bc the answers here use the formula: P(A U B) = P(A) + P(B) - P(A and B)

Should I use the NOT independent events formula: P(AnB) = P(A).P(B|A)?

Thanks
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guireif
When the question says "not independent", what should I do?

Should I consider that the events are NOT mutually exclusive? Is it the same? Bc the answers here use the formula: P(A U B) = P(A) + P(B) - P(A and B)

Should I use the NOT independent events formula: P(AnB) = P(A).P(B|A)?

Thanks


I have the same doubt.
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robertops
guireif
When the question says "not independent", what should I do?

Should I consider that the events are NOT mutually exclusive? Is it the same? Bc the answers here use the formula: P(A U B) = P(A) + P(B) - P(A and B)

Should I use the NOT independent events formula: P(AnB) = P(A).P(B|A)?

Thanks


I have the same doubt.

I don't believe I've seen this language (dependent vs independent) on an official question, so I don't believe it's tested on the actual GMAT. However, if anyone does know of an example, please post it, thanks.
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Why is this question not taking into account P(AUB)`?

Shouldn't the equation be P(A) + P(B) - P(AnB) + P(AUB)`?
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Bunuel
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Suppose A and B are two events that are not independent. Is the probability P(A and B) > 1/3?

(1) P(A) = 0.8 and P(B) = 0.7
(2) P(A or B) = 0.9


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MAGOOSH OFFICIAL SOLUTION:

Statement #1: this is very tricky. There is no cut-and-dry probability rule for this. we have to think about overlap. The total probability space, which encompasses anything that possibly could happen, has a size of 1, and P(A) and P(B) have to fit in this space. These two have a size of 0.8 and 0.7 respectively, so they are going to overlap. Think about it visually —
Attachment:
gdspqop_img4.png

Push the P(A) = 0.8 all the way to the left (whatever that means!), leaving the 0.2 outside of A on the right. Now, push P(B) = 0.7 all the way to the right, leaving the 0.3 outside of B on the left. Suppose the 0.2 outside of A is inside B, and the 0.03 outside of B is inside A. This would be the minimum possible overlap, and even then the overlap, P(A and B), equals 0.5. Thus, P(A and B) ≥ 0.5, so it must be greater than 1/3. this statement allows us to give a definitive answer to the prompt question. This statement, alone and by itself, is sufficient.

Statement #2: forget everything we learned in the analysis of statement (1). Now, all we know is P(A or B) = 0.9, and we know absolutely nothing about P(A) or P(B). We can calculate nothing else. This statement, alone and by itself, is insufficient.

First sufficient, second not sufficient.

Answer = A.

Bunuel, when I think about the overlapping set, we should have:
P (A or B) + P (A and B) = 1
=> P (A and B) = 1 - 0.9 = 0.1
=> B is sufficient
Is that right?
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robertops
guireif
When the question says "not independent", what should I do?

Should I consider that the events are NOT mutually exclusive? Is it the same? Bc the answers here use the formula: P(A U B) = P(A) + P(B) - P(A and B)

Should I use the NOT independent events formula: P(AnB) = P(A).P(B|A)?

Thanks


I have the same doubt.

I don't believe I've seen this language (dependent vs independent) on an official question, so I don't believe it's tested on the actual GMAT. However, if anyone does know of an example, please post it, thanks.

Hello, I don't quite understand the responses.

The question states 2 things:
1. Non-independence
2. P(A AND B) ..."and" means multiply

So the formula is necessarily: P(A and B) = P(A) x P(B | A) as far as I understand it.

Why are others using the addition formula? The question isn't asking about P(A OR B)?

Bunuel can you clarify this important distinction?

Also, how would one go about calculating P(B | A) or (P(A | B))?

Edit: I just checked...regarding my last question, conditional probabilities are calculated like so:

1. P(A|B) = P(A and B) / P(B)
2. P(B|A) = P(A and B) / P(A)

However, I don't understand why neither of these were applied in this question...
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The wording of the question "not independent" should result only in (E), unless P(A|B) is known
If the dependence is not known P(A and B) cannot be determined.

The logic used in the OA is that for "not exclusive", the same cannot be applied if events depend on each other.
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Bunuel if the events are not independent doesn't this mean that they could potentially be mutually exclusive?
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