A biased coin having probability of tails appearing as 3 2 is tossed. If heads appears, 4 letters are chosen at random without replacement from the word CHRISTMAS, and if tails appears, 5 letters are chosen at random without replacement from the same word. Given that the chosen letters contain no S, the probability that tail appeared on the coin can be written as b a , where a and b are coprime integers. Find a + b .
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Let T be the event that the coin is tails and H be the event that it is heads.
We know that P ( T ) = 3 2 and P ( H ) = 3 1
We have to find
P ( T ∣ Letters had no S ) .
Now, P ( T ∣ Letters had no S ) = P ( Letters had no S ) P ( Letters had no S ∣ T ) × P ( T )
P ( Letters had no S ∣ T ) = ( 5 9 ) ( 5 7 ) = 1 2 6 2 1
P ( Letters had no S ∣ H ) = ( 4 9 ) ( 4 7 ) = 1 2 6 3 5
And P ( Letters had no S ) = P ( Letters had no S ∣ T ) × P ( T ) + P ( Letters had no S ∣ H ) × P ( H )
Thus finally we get
P ( Letters had no S ∣ T ) = 1 2 6 2 1 × 3 2 + 1 2 6 3 5 × 3 1 1 2 6 2 1 × 3 2 = 1 1 6 which gives us 6 + 1 1 = 1 7
In the last part, I meant to write P ( T ∣ Letters had no S ) and not the other way round. That's what we had to find.
Let S be the event that the chosen letters contain no S, h the event that head appeared on the coin, and t the event that tail appeared on the coin. By Bayes' formula, the probability of t given S is P ( S ) P ( t ∩ S ) . We calculate the numerator and denominator separately.
First we calculate P ( t ∩ S ) . The probability of getting tails is 3 2 . Once we have flipped tails, we must only get the 7 letters that are not S. We can choose these letters in ( 5 7 ) = 2 1 ways. Thus we have P ( t ∩ S ) = 3 2 ⋅ 2 1 = 1 4 .
Now we calculate P ( S ) . Note that h and t are complementary events, so that P ( S ) = P ( h ∩ S ) + P ( t ∩ S ) . We have already calculated P ( t ∩ S ) to be 1 4 . We can count P ( h ∩ S ) in a similar way. There is a 3 1 chance of getting heads. Once we have flipped heads, we must choose only the 7 non-S letters in our 4 pickings; this can be done in ( 4 7 ) = 3 5 ways. Thus P ( h ∩ S ) = 3 1 ⋅ 3 5 .
Now we have that P ( t ∣ S ) = 1 4 + 3 3 5 1 4 = 3 4 2 + 3 3 5 3 4 2 = 7 7 4 2 = 1 1 6 . Thus a + b = 6 + 1 1 = 1 7 .
awesome explanation
how can any probability exceed 1
If there are no S 's then the number of ways of choosing 4 from 7 is ( 4 7 ) = 35 and the number of ways of choosing 5 letters from 7 is ( 5 7 ) = 2 1
So if we get tails we have 2 1 ways of getting a combination with no S
And if we get heads we have 3 5 ways of getting a combination with no S
We expect the ratio to be 2 1 ∗ 2 : 3 5 however because a tails is twice as likely.
i.e. a ratio of 6 : 5 so the probability is 1 1 6 so a + b = 6 + 1 1 = 1 7
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Let S ′ be the event of non-occurrence of S, T & H be the events of getting a tail & head respectively. Then using traditional Bayes' theorem, we have:
P ( T / S ′ ) = P ( S ′ / T ) × P ( T ) + P ( S ′ / H ) × P ( H ) P ( S ′ / T ) × P ( T ) = 1 1 6 after substituting values.