Question:

Bag I contains 3 red, 4 black and 3 white balls and Bag II contains 2 red, 5 black and 2 white balls. One ball is transferred from Bag I to Bag II and then a ball is drawn from Bag II. The ball so drawn is found to be black in colour. Then the probability, that the transferred ball is red, is :

Updated On: Feb 5, 2026
  • \(\frac{4}{9}\)
  • \(\frac{5}{18}\)
  • \(\frac{1}{6}\)
  • \(\frac{3}{10}\)
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The Correct Option is B

Approach Solution - 1

The given problem involves probability with conditional events and can be solved using the concept of conditional probability.

First, let's define the scenario:

  • Bag I contains 3 red, 4 black, and 3 white balls, totaling 10 balls.
  • Bag II contains 2 red, 5 black, and 2 white balls, totaling 9 balls initially.

Let's consider the events:

  • \(A\): The event that a red ball is transferred from Bag I to Bag II.
  • \(B\): The event that the ball drawn from Bag II is black.

We need to find \(P(A \mid B)\), the probability that a red ball was transferred given that a black ball is drawn.

By Bayes' Theorem, \(P(A \mid B) = \frac{P(B \mid A) \cdot P(A)}{P(B)}\).

Step 1: Calculate \(P(A)\)

The probability of transferring a red ball from Bag I, \(P(A)\), is:

P(A) = \frac{\text{Number of red balls in Bag I}}{\text{Total number of balls in Bag I}} = \frac{3}{10}

Step 2: Calculate \(P(B \mid A)\)

Given that a red ball is transferred to Bag II, the composition of Bag II becomes:

  • 3 red balls,
  • 5 black balls,
  • 2 white balls.

The probability of drawing a black ball from Bag II in this case is:

P(B \mid A) = \frac{5}{10} = \frac{1}{2}

Step 3: Calculate \(P(B)\)

\(P(B)\) is the probability of drawing a black ball considering both possibilities (transferred ball is red, black, or white):

P(B) = P(B \mid A) \cdot P(A) + P(B \mid A') \cdot P(A')

  • Where \(A'\): Event that a non-red ball is transferred (either black or white).

For \(A'\):

P(A') = 1 - P(A) = \frac{7}{10}

If a black ball is transferred:

  • 5 red balls,
  • 6 black balls,
  • 2 white balls in Bag II
P(B \mid A', \text{transfer black}) = \frac{6}{11}

If a white ball is transferred:

  • 2 red balls,
  • 5 black balls,
  • 3 white balls in Bag II
P(B \mid A', \text{transfer white}) = \frac{5}{11}

P(A'\text{ and transfer black}) = \frac{4}{10} and P(A'\text{ and transfer white}) = \frac{3}{10}

So,

P(B) = \frac{1}{2} \cdot \frac{3}{10} + \frac{6}{11} \cdot \frac{2}{5} + \frac{5}{11} \cdot \frac{3}{10}

= \frac{3}{20} + \frac{12}{55} + \frac{15}{110} = \frac{51}{110}

Step 4: Calculate \(P(A \mid B)\)

P(A \mid B) = \frac{P(B \mid A) \cdot P(A)}{P(B)} = \frac{\frac{1}{2} \cdot \frac{3}{10}}{\frac{51}{110}}

= \frac{3}{20} \times \frac{110}{51} = \frac{5}{18}

Therefore, the probability that the transferred ball was red, given that a black ball was drawn from Bag II, is \(\frac{5}{18}\).

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Approach Solution -2

Let E→Ball drawn from Bag II is black.
ER→Bag I to Bag II red ball transferred.
EB→Bag I to Bag II black ball transferred.
EW→Bag I to Bag II white ball transferred.
 

\(P(\frac{E_R}{E})=\frac{P(\frac{E}{ER})⋅P(ER) }{ P(\frac{E}{ER})P(ER)+P(\frac{E}{EB})⋅P(EB)+P(\frac{E}{EW})P(EW)}\)


Here,
P(ER)=\(\frac{3}{10}\), P(EB)=\(\frac{4}{10}\), P(EW)=\(\frac{3}{10}\)
and
 \(P(\frac{E}{E_R})=\frac{5}{10},P(\frac{E}{E_B})=\frac{5}{10},P(\frac{E}{E_W})=\frac{5}{10}\)

\(∴P(\frac{E_R}{E})=\frac{\frac{15}{100} }{\frac{ 15}{100}+\frac{24}{100}+\frac{15}{100}}\)
=\(\frac{15}{54}\)
\(=\frac{5}{18}\)
So, the correct option is (B): \(\frac{5}{18}\)

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Concepts Used:

Conditional Probability

Conditional Probability is defined as the occurrence of any event which determines the probability of happening of the other events. Let us imagine a situation, a company allows two days’ holidays in a week apart from Sunday. If Saturday is considered as a holiday, then what would be the probability of Tuesday being considered a holiday as well? To find this out, we use the term Conditional Probability.

Let’s discuss certain theorems of Conditional Probability:

  1. Let us consider a random experiment where the sample space S is considered as space and two events namely A and B happen there. Then, the formula would be:

P(S | B) = P(B | B) = 1.

Proof of the same: P(S | B) = P(S ∩ B) ⁄ P(B) = P(B) ⁄ P(B) = 1.

[S ∩ B indicates the outcomes common in S and B equals the outcomes in B].

  1. Now let us consider any two events namely A and B happening in a sample space ‘s’, then, P(A ∩ B) = P(A).

P(B | A), P(A) >0 or, P(A ∩ B) = P(B).P(A | B), P(B) > 0.

This theorem is named as the Multiplication Theorem of Probability.

Proof of the same: As we all know that P(B | A) = P(B ∩ A) / P(A), P(A) ≠ 0.

We can also say that P(B|A) = P(A ∩ B) ⁄ P(A) (as A ∩ B = B ∩ A).

So, P(A ∩ B) = P(A). P(B | A).

Similarly, P(A ∩ B) = P(B). P(A | B).

The interesting information regarding the Multiplication Theorem is that it can further be extended to more than two events and not just limited to the two events. So, one can also use this theorem to find out the conditional probability in terms of A, B, or C.

Read More: Types of Sets

 

Sometimes students get confused between Conditional Probability and Joint Probability. It is essential to know the differences between the two.