There are 2 balls in a bag. Each of which is either Green or Red (with equal odds).
You add 1 red ball to the bag, and then take 1 out at random. It's Red.
You add 1 red ball to the bag, and then take 1 out at random. It's Red.
You add 3 red balls to the bag, and then take 3 out at random. They are all Red.
Let b a be the probability the original balls were both Red, (where a and b are coprime).
What is a + b ?
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Why is P(E l GG) = 1/3 * 1/3 * 1/10 I am confused with the 1/10 part
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If there are three red balls and two green balls in a bag, the probability of three random balls from the bag all being red is 1 / 1 0 . This is because ( 3 5 ) = 1 0 .
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Shouldn't it be 3/5
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@Saket Goyal – There are ( 3 5 ) ways to choose three balls from the bag, and only one of them gives all red balls.
Let's go through all cases: Both Green: Adding N Red balls, taking N out at random and them all being Red, has probability ( N + 2 ) ( N + 1 ) 2 . (Probability of picking 2 Green balls to be left).
One Red, One Green (twice as likely): Adding N Red balls, taking N out at random and them all being Red, has probability ( N + 2 ) 2 . (Probability of picking 1 Green balls with 2 picks to be left).
Both Red: Adding N Red balls, taking N out at random and them all being Red, has probability 1 .
Ratios are:
2 : 2 ∗ 2 ( N + 1 ) : ( N + 2 ) ( N + 1 )
Doing this multiple times, with N = a , b , c gives the ratio:
2 3 : 2 ∗ 2 3 ( a + 1 ) ( b + 1 ) ( c + 1 ) : ( a + 2 ) ( a + 1 ) ( b + 2 ) ( b + 1 ) ( c + 2 ) ( c + 1 )
Setting a = b = 1 , c = 3 :
2 3 : 2 ∗ 2 3 ∗ 2 4 : 2 4 ∗ 4 5 = = 1 : 3 2 : 9 0
So the odds that both balls were Red are: 1 2 3 9 0 = 4 1 3 0
You start out with rr, gg or gr with respective probabilities 1/4, 1/4 and 2/4.
After adding a red ball and randomly retrieving a ball, what are the chances you retrieve a red ball?
P(r|gg)=1/3
P(r|rr)=1
P(r|gr)=2/3
After that, the situation is back to what it was before you did this. So doing this three times in a row gives these chances:
P(3 times r|gg)=1/27
P(3 times r|rr)=1
P(3 times r|gr)=8/27
P(3 times r AND gg) =1/4*1/27=1/108
P(3 times r AND rr) =1/4*1=1/4=27/108
P(3 times r AND gr) =1/2*8/27=16/108
Therfore p(3 times r) =(1+27+16)/108
P(3 times r AND rr) = P(3 times r) *P(rr|3 times r)
27/108=44/108*P(rr|3 times r)
P(rr|3 times r)=27/44
The answer is 27+44=71.
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Let's let the event be E . Then Bayes' theorem says P ( R R ∣ E ) = P ( E ) P ( E ∣ R R ) P ( R R ) . Now P ( E ∣ R R ) = 1 , and P ( R R ) = 1 / 4 , so the only difficult calculation is P ( E ) .
But P ( E ) = P ( E ∣ G G ) P ( G G ) + P ( E ∣ G R ) P ( G R ) + P ( E ∣ R R ) P ( R R ) , and P ( E ∣ G G ) P ( G G ) P ( E ∣ G R ) P ( G R ) P ( E ∣ R R ) P ( R R ) = 3 1 ⋅ 3 1 ⋅ 1 0 1 = 4 1 = 3 2 ⋅ 3 2 ⋅ 5 2 = 2 1 = 1 = 4 1 so we get P ( R R ∣ E ) = 1 / 3 6 0 + 4 / 4 5 + 1 / 4 1 / 4 = 4 1 3 0 , so the answer is 7 1 .