MCQMediumJEE 2026Conditional Probability & Bayes Theorem

JEE Mathematics 2026 Question with Solution

A bag contains 1010 balls out of which kk are red and (10k)(10-k) are black, where 0k100 \le k \le 10. If three balls are drawn at random without replacement and all of them are found to be black, then the probability that the bag contains 11 red and 99 black balls is:

  • A

    711\dfrac{7}{11}

  • B

    755\dfrac{7}{55}

  • C

    1455\dfrac{14}{55}

  • D

    7110\dfrac{7}{110}

Answer

Correct answer:B

Step-by-step solution

Standard Method

Given: A bag contains 1010 balls with kk red and (10k)(10-k) black, where 0k100 \le k \le 10. Three balls are drawn without replacement and all are black.

Find: The posterior probability that the bag contains 11 red and 99 black balls.

Concept: This is a Bayes' theorem problem.

Let

Ek=Event that the bag contains k red ballsE_k = \text{Event that the bag contains } k \text{ red balls}

and

A=Event that all three drawn balls are blackA = \text{Event that all three drawn balls are black}

Since no prior information is given, all values k=0,1,2,,10k = 0,1,2,\ldots,10 are equally likely, so

P(Ek)=111P(E_k) = \frac{1}{11}

Number of black balls when there are kk red balls is (10k)(10-k). Therefore,

P(AEk)=(10k3)(103)P(A\mid E_k) = \frac{\binom{10-k}{3}}{\binom{10}{3}}

Now apply Bayes' theorem:

P(E1A)=P(AE1)P(E1)k=07P(AEk)P(Ek)P(E_1\mid A) = \frac{P(A\mid E_1)P(E_1)}{\sum_{k=0}^{7} P(A\mid E_k)P(E_k)}

The upper limit is 77 because for k>7k>7, fewer than 33 black balls are available. Thus,

P(E1A)=(93)k=07(10k3)P(E_1\mid A) = \frac{\binom{9}{3}}{\sum_{k=0}^{7} \binom{10-k}{3}}

So,

P(E1A)=84(103)+(93)+(83)+(73)+(63)+(53)+(43)+(33)P(E_1\mid A) = \frac{84}{\binom{10}{3} + \binom{9}{3} + \binom{8}{3} + \binom{7}{3} + \binom{6}{3} + \binom{5}{3} + \binom{4}{3} + \binom{3}{3}} =84120+84+56+35+20+10+4+1= \frac{84}{120 + 84 + 56 + 35 + 20 + 10 + 4 + 1} =84330=755= \frac{84}{330} = \frac{7}{55}

Therefore, the required probability is 755\dfrac{7}{55}, so the correct option is B.

Bayes Theorem Expansion

Given: The event observed is that all three drawn balls are black.

Find: P(E1A)P(E_1\mid A).

Bayes' theorem gives

P(E1A)=P(AE1)P(E1)P(A)P(E_1\mid A) = \frac{P(A\mid E_1)P(E_1)}{P(A)}

Since each possible value of kk from 00 to 1010 is equally likely,

P(Ek)=111P(E_k)=\frac{1}{11}

For a fixed kk, the probability that all three drawn balls are black is

P(AEk)=(10k3)(103)P(A\mid E_k)=\frac{\binom{10-k}{3}}{\binom{10}{3}}

Hence,

P(A)=k=07P(AEk)P(Ek)P(A)=\sum_{k=0}^{7} P(A\mid E_k)P(E_k)

Substituting in Bayes' theorem, the common factor 111(103)\frac{1}{11\binom{10}{3}} cancels, giving

P(E1A)=(93)k=07(10k3)P(E_1\mid A)=\frac{\binom{9}{3}}{\sum_{k=0}^{7}\binom{10-k}{3}}

Now evaluate:

(93)=84\binom{9}{3}=84

and

k=07(10k3)=(103)+(93)+(83)+(73)+(63)+(53)+(43)+(33)\sum_{k=0}^{7}\binom{10-k}{3}=\binom{10}{3}+\binom{9}{3}+\binom{8}{3}+\binom{7}{3}+\binom{6}{3}+\binom{5}{3}+\binom{4}{3}+\binom{3}{3} =120+84+56+35+20+10+4+1=330=120+84+56+35+20+10+4+1=330

Therefore,

P(E1A)=84330=755P(E_1\mid A)=\frac{84}{330}=\frac{7}{55}

Thus the correct option is B.

Common mistakes

  • Assuming the required probability is only P(AE1)P(A\mid E_1) is incorrect. The question asks for a posterior probability after observing three black balls, so Bayes' theorem must be used. Compute P(E1A)P(E_1\mid A), not just the likelihood of the observation.

  • Summing the denominator over all k=0k=0 to 1010 without checking feasibility is wrong. If k>7k>7, then the bag has fewer than 33 black balls, so drawing three black balls is impossible. Restrict the sum to k=0k=0 through 77.

  • Forgetting the equal prior assumption leads to an incomplete setup. Since no prior information is given, all values of kk are taken equally likely, so P(Ek)=111P(E_k)=\frac{1}{11} for each admissible case before applying Bayes' theorem.

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