Q.Bag I contains 3 red and 4 black balls and Bag II contains 4 red and 5 black 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 red in colour. Find the probability that the transferred ball is black.
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🔒 Start your 14-day free trial to unlock the full solution →Concept understanding — Conditional Probability
Conditional Probability
Roll a die and ask "what is the chance of an even number?" — that is 3/6. But suppose someone tells you the result is greater than 3. Now you are no longer looking at all six faces, only at {4,5,6}, and two of those (4 and 6) are even, so the probability becomes 2/3. That change — from the probability of A to the probability of A given that B has already occurred — is conditional probability.
The Idea: Shrink the Sample Space
Conditioning on B throws away every outcome where B is false and treats B as the new "whole world." You measure A only against what is still possible.
Think of filtering a table of data: unconditional probability uses every row; conditional probability keeps only the rows where the condition is true.
The Definition
For events A and B with P(B)>0,
P(A∣B)=P(B)P(A∩B).
We divide by P(B) to rescale so that B itself has probability 1; the surviving part of A is the overlap A∩B. Checking the die: P(A∩B)=P({4,6})=62 and P(B)=63, so P(A∣B)=3/62/6=32, matching the intuition.
Rearranging gives the multiplication rule P(A∩B)=P(A∣B)P(B), which is usually the easier way to compute a joint probability when a problem says "given that."
Two Cautions
- P(A∣B) and P(B∣A) are generally not equal; swapping them is the classic mistake. They are linked by Bayes' theorem, P(A∣B)=P(B)P(B∣A)P(A). …
Idea: This is a Bayes' theorem problem. The transferred ball is the unknown "cause"; drawing a red from Bag II is the observed "effect."
Let E1 = red transferred, E2 = black transferred, A = ball drawn from Bag II is red.
Priors (from Bag I: 3 red, 4 black): P(E1)=73, P(E2)=74.
Likelihoods (Bag II starts with 4 red, 5 black; total becomes 10 after transfer):
- Red transferred ⇒ 5 red of 10: P(A∣E1)=105.
- Black transferred ⇒ 4 red of 10: P(A∣E2)=104. …
Given that a red ball was drawn from Bag II, Bayes' theorem gives the probability that the transferred ball was black as 3116.
The setup
One ball is moved from Bag I (3 red, 4 black) into Bag II (4 red, 5 black), and then a ball is drawn from Bag II and turns out to be red. We want the chance that the ball we transferred was black. Two hidden possibilities ("red transferred" or "black transferred") could have led to the same visible outcome ("red drawn"), so this is a Bayes' theorem question.
Define:
- E1: the transferred ball is red
- E2: the transferred ball is black
- A: the ball drawn from Bag II is red
We want P(E2∣A).
Step 1 — prior probabilities
Bag I has 3+4=7 balls, so
P(E1)=73,P(E2)=74.
Step 2 — likelihoods after the transfer
Bag II starts with 4 red and 5 black (9 balls); adding one ball makes 10.
If a red was transferred, Bag II has 5 red and 5 black:
P(A∣E1)=105=21.
If a black was transferred, Bag II has 4 red and 6 black:
P(A∣E2)=104=52.
Step 3 — apply Bayes' theorem
P(E2∣A)=P(E1)P(A∣E1)+P(E2)P(A∣E2)P(E2)P(A∣E2). …
Method: Bayes' Theorem for a transfer-then-draw problem
Use this when an unseen item is moved from one bag to another, a draw is then made from the second bag, and you must judge what the transferred item was.
Steps
Step 1: Make the hidden transfer the set of hypotheses.
The unknown is the colour transferred; list those cases Hi with priors equal to the composition of the source bag.
Step 2: Update the receiving bag for each case, then read the draw likelihood.
Add the transferred item to the second bag — its total count goes up by one — and recompute P(E∣Hi), the chance of the observed draw for that case. Forgetting to update the count (and the total) is the classic slip. …
Common Mistakes
Mistake 1: Not updating Bag II's count after the transfer.
Why it's wrong: after one ball is added, Bag II holds 10, not 9; the draw likelihoods are read from the 10-ball bag. Correct approach: red transferred ⇒ 5 red of 10; black transferred ⇒ 4 red of 10.
Mistake 2: Taking the priors from Bag II instead of Bag I.
Why it's wrong: the transferred ball's colour is governed by Bag I's composition (3 red, 4 black). Correct approach: P(red transferred)=73, P(black transferred)=74. …
Showing the 12 most recent of 69 on this concept.
- AP EAPCET 2024Set eng-2024-05-19-AN1 markMCQQ.There are 2 bags each containing 3 white and 5 black balls and 4 bags each containing 6 white and 4 black balls. If a ball drawn randomly from a bag is found to be black, then the probability that this ball is from the first set of bags is (A) 5725 (B) 4125 (C) 52 (D) 53
›Reveal solutionSolution
A classic Bayes'-theorem (inverse-probability) question: given the ball drawn is black, find the probability it came from the first group of bags. Answer: 5725.
Concept and Intuition
When an experiment happens in two stages — first a bag is picked (from one of two groups of bags), then a ball is drawn from it — and we're told the result of the second stage (a black ball came out), Bayes' theorem lets us reverse the direction of reasoning and find the probability about the first stage (which group the bag was from). The prior probability of picking from a group is proportional to how many bags are in that group (each individual bag is equally likely to be picked), and then we weight by how likely that group is to produce the observed outcome.
Step-by-Step Solution
- Groups and priors. Group 1 (call it S1) has 2 bags (each 3 white, 5 black — 8 balls). Group 2 (S2) has 4 bags (each 6 white, 4 black — 10 balls). Total bags =6, each equally likely to be chosen, so
P(S1)=62=31,P(S2)=64=32.
- Likelihoods of drawing black. From a group-1 bag: P(B∣S1)=85. From a group-2 bag: P(B∣S2)=104=52.
- Total probability of drawing a black ball (law of total probability): P(B)=P(S1)P(B∣S1)+P(S2)P(B∣S2)=31⋅85+32⋅52=245+154. …
- AP EAPCET 2024Set eng-2024-05-23-FN1 markMCQQ.Bag A contains 2 white and 3 red balls and bag B contains 4 white and 5 red balls. If one ball is drawn at random from one of the bags and is found to be red, then the probability that it was drawn from the bag B is (A) 5423 (B) 5125 (C) 5225 (D) 5527
›Reveal solutionSolution
A classic Bayes'-theorem problem: given the ball drawn is red, the probability it came from bag B is 5225.
Concept and Intuition
This is Bayes' theorem: we're given the outcome (red ball drawn) and want to find the probability of which "cause" (bag A or B) produced it, using the prior probability of choosing each bag (each 21) and each bag's own probability of yielding red.
Step-by-Step Solution
- Bag A: 2 white, 3 red (5 total) ⇒P(red∣A)=53.
- Bag B: 4 white, 5 red (9 total) ⇒P(red∣B)=95.
- P(A)=P(B)=21 (bag chosen at random).
- Total probability of red: P(red)=P(A)P(red∣A)+P(B)P(red∣B)=21⋅53+21⋅95=103+185.
- Common denominator 90: 103=9027, 185=9025, sum =9052=4526.
- Bayes: P(B∣red)=P(red)P(B)P(red∣B)=26/45(1/2)(5/9)=26/455/18. …
- AP EAPCET 2022Set eng-2022-07-05-FN1 markMCQQ.A bag contains 4 red and 3 black balls. A second bag contains 2 red and 3 black balls. One bag is selected at random. If from the selected bag, one ball is drawn at random, then the probability that the ball drawn is red is (A) 7039 (B) 7041 (C) 7029 (D) 3517
›Reveal solutionSolution
Total probability theorem over the two equally-likely bags gives 3517.
Concept and Intuition
Since the bag is chosen at random (each with probability 21), the overall probability of drawing red is the weighted average of the conditional probabilities of drawing red from each bag.
Step-by-Step Solution
- Bag 1: 4 red, 3 black (7 total) → P(red∣Bag1)=74.
- Bag 2: 2 red, 3 black (5 total) → P(red∣Bag2)=52.
- P(red)=21⋅74+21⋅52=144+102=72+51. …
- AP EAPCET 2026Set eng-2026-05-12-AN1 markMCQQ.A bag 'A' contains 2 black and 3 white balls. Another bag 'B' contains 3 black and 2 white balls. Two balls are drawn randomly from 'A' and placed in 'B'. Later, if two balls are drawn randomly from 'B', then the probability of getting a black ball and a white ball from it is (A) 10559 (B) 10546 (C) 21059 (D) 21067
›Reveal solutionSolution
A two-stage random-transfer problem — condition on what got transferred from A to B, then apply the law of total probability.
Concept and Intuition
Since the composition of bag B after the transfer depends on which 2 balls were drawn from A, we must split into the three possible transfer outcomes (BB, BW, WW), compute the probability of each, then the conditional probability of drawing one black and one white ball from the resulting bag B, and combine via the law of total probability.
Step-by-Step Solution
- Bag A has 5 balls (2B, 3W); ways to choose 2: (25)=10.
- P(BB from A)=(22)/(25)=1/10.
- P(BW from A)=(12)(13)/(25)=6/10=3/5.
- P(WW from A)=(23)/(25)=3/10.
- Bag B originally has 3B, 2W (5 balls); after adding 2 balls it has 7 balls, and we want P(1B,1W) drawn from it: (27)=21 ways.
- If BB added: B = 5B, 2W. P(1B,1W)=(15)(12)/21=10/21.
- If BW added: B = 4B, 3W. P(1B,1W)=(14)(13)/21=12/21.
- If WW added: B = 3B, 4W. P(1B,1W)=(13)(14)/21=12/21.
- Total probability: …
- Bag A has 5 balls (2B, 3W); ways to choose 2: (25)=10.
- AP EAPCET 2025Set eng-2025-05-23-AN1 markMCQQ.A bag contains 5 balls of unknown colours. There are equal chances that out of these five balls, there may be 0 or 1 or 2 or 3 or 4 or 5 red balls. A ball is taken out from the bag at random and is found to be red. The probability that it is the only red ball in the bag is (A) 51 (B) 61 (C) 151 (D) 301
›Reveal solutionSolution
This is a Bayes'-theorem problem over the six equally likely compositions of red balls; the posterior probability that exactly one ball is red, given a red ball was drawn, is 1/15.
Concept and Intuition
Bayes' theorem updates the prior (uniform belief over how many red balls there are) using the evidence (a red ball was drawn) — compositions with more red balls make drawing red more likely, so they get more posterior weight, but we want specifically the R=1 case.
Step-by-Step Solution
- Prior: P(R=r)=61 for r=0,1,2,3,4,5.
- Likelihood of drawing red given R=r red balls among 5: P(red∣R=r)=5r.
- Total probability of drawing red: P(red)=∑r=0561⋅5r=301(0+1+2+3+4+5)=3015=21. …
- AP EAPCET 2026Set eng-2026-05-13-FN1 markMCQQ.Bag A contains 3 white and 4 black balls. Bag B contains 4 white and 3 black balls. Bag C contains 2 white and 5 black balls. A bag is randomly selected and then a ball is randomly drawn from that bag. If the ball drawn was found to be white, then the probability that the ball is drawn from bag C is (A) 61 (B) 92 (C) 41 (D) 132
›Reveal solutionSolution
This is a direct Bayes'-theorem (inverse probability) question. Answer: 92.
Concept and Intuition
We're given the outcome (a white ball was drawn) and asked for the probability of a particular cause (it came from bag C). This is exactly Bayes' theorem: P(C∣W)=∑iP(bagi)P(W∣bagi)P(C)P(W∣C).
Step-by-Step Solution
- Each bag is chosen with probability 31.
- P(W∣A)=73 (3 white out of 7 total in bag A).
- P(W∣B)=74 (4 white out of 7 in bag B).
- P(W∣C)=72 (2 white out of 7 in bag C).
- Total probability of white: P(W)=31(73+74+72)=31⋅79=219=73. …
- AP EAPCET 2026Set eng-2026-05-15-AN1 markMCQQ.A bag P contains 5 white and 4 blue balls. Another bag Q contains 4 white and 5 blue balls. A bag is randomly selected and a ball is drawn at random. If the ball selected from that bag is transferred to another bag, then the probability that bag Q has same number of blue and white balls is (A) 2/9 (B) 1/9 (C) 5/9 (D) 4/9
›Reveal solutionSolution
This tests conditional probability with a transfer-between-bags setup; you must track which single transfer restores balance to bag Q, in both directions of transfer. Answer: 5/9.
Concept and Intuition
A ball moves from whichever bag is picked into the other bag. "Bag Q ends up balanced" can happen two structurally different ways: either Q gains a ball (if P was picked) or Q loses a ball (if Q was picked). Each scenario needs the transferred ball to be a specific colour for Q's counts to equalize, so we compute each scenario's probability and add them (mutually exclusive cases, law of total probability).
Step-by-Step Solution
- Bag P: 5W,4B (9 total). Bag Q: 4W,5B (9 total).
- Scenario A (P picked, prob 1/2): a ball moves P→Q, so Q becomes a 10-ball bag. Q needs to end at 5W,5B. Since Q started 4W,5B, the incoming ball must be white. P(white∣P)=5/9. Probability of this scenario succeeding: 21×95=185. …
- AP EAPCET 2025Set eng-2025-05-22-AN1 markMCQQ.An urn A contains 4 white and 1 black ball; urn B contains 3 white and 2 black balls and urn C contains 2 white and 3 black balls. One ball is transferred randomly from A to B; later one ball is transferred randomly from B to C. Finally, if a ball is drawn randomly from C, then the probability that it is a black ball is (A) 127 (B) 18089 (C) 180101 (D) 3617
›Reveal solutionSolution
A two-stage transfer-then-draw problem, solved by branching over all four possible transfer outcomes: probability of black =180101.
Concept and Intuition
This is a sequential conditional-probability problem: each transfer changes the composition of the receiving urn, so we must branch over every possible outcome of each transfer and weight the final draw accordingly (total probability theorem, applied twice).
Step-by-Step Solution
- Urn A: 4W,1B. Transfer to B: P(W)=54, P(B)=51.
- If white moved to B: B becomes 4W,2B (6 balls). If black moved to B: B becomes 3W,3B (6 balls).
- From B (4W,2B): transfer white to C with P=64=32 (C becomes 3W,3B), or black with P=62=31 (C becomes 2W,4B).
- From B (3W,3B): transfer white to C with P=21 (C becomes 3W,3B), or black with P=21 (C becomes 2W,4B).
- Final draw from C: P(black∣3W3B)=21; P(black∣2W4B)=64=32.
- Combine all four branches:
- A-white, B-white: 54⋅32⋅21=308=154
- A-white, B-black: 54⋅31⋅32=458 …
- AP EAPCET 2023Set eng-2023-05-17-AN1 markMCQQ.Three boxes B1, B2 and B3 contain balls with different colors as follows:A die is thrown. Box B1 is chosen if either 1 or 2 turns up. Box B2 is chosen if 3 or 4 turns up and box B3 is chosen if 5 or 6 turns up. Having chosen a box in this way, a ball is drawn at random from that box. If the ball drawn is found to be Red, then the probability that it is drawn from box B2 is (A) 127 (B) 125 (C) 121 (D) 263
White Black Red B1 2 1 2 B2 3 2 4 B3 4 3 2 ›Reveal solutionSolution
A Bayes'-theorem problem: reverse the conditional probability "ball is Red, which box?" using the total-probability formula.
Concept and Intuition
Bayes' theorem lets us "invert" a conditional probability. We know P(Red∣Bi) for each box and the prior P(Bi) (each 1/3 since the die is fair and each box corresponds to two faces); we want the posterior P(B2∣Red).
Step-by-Step Solution
- Totals in each box: B1: 2+1+2=5; B2: 3+2+4=9; B3: 4+3+2=9.
- P(Red∣B1)=52, P(Red∣B2)=94, P(Red∣B3)=92.
- Each box has prior probability 31 (each box corresponds to two die faces out of six).
- Total probability: P(Red)=31(52+94+92)=31(52+32)=31⋅1516=4516. …
- AP EAPCET 2024Set eng-2024-05-19-AN1 markMCQQ.A bag contains 2 white, 3 green and 5 red balls. If three balls are drawn one after the other without replacement, then the probability that the last ball drawn was red is (A) 32 (B) 43 (C) 95 (D) 21
›Reveal solutionSolution
By the symmetry of random sampling without replacement, the probability that the last ball drawn is red equals the overall fraction of red balls in the bag: 105=21.
Concept and Intuition
When balls are drawn one after another without replacement, every ball is equally likely to occupy any given position in the drawing order (all 10! orderings of the bag's balls are equally likely). Hence the marginal probability that the ball in any fixed position (first, second, ..., last) is red is just (number of red balls)/(total balls), independent of which position we pick.
Step-by-Step Solution
- Bag: 2 white +3 green +5 red =10 balls total.
- Consider a full random permutation of all 10 balls (drawing three is just looking at the first three positions of such a permutation, but the argument works for any position).
- By symmetry, P(ball in position k is red)=105 for every position k, including the third (last) position drawn here. …
- AP EAPCET 2024Set eng-2024-05-22-FN1 markMCQQ.A bag contains 6 balls. If three balls are drawn at a time and all of them are found to be green, then the probability that exactly 5 of the balls in the bag are green is: (A) 354 (B) 355 (C) 72 (D) 71
›Reveal solutionSolution
This is a Bayes'-theorem problem: given a uniform prior on the unknown number of green balls in the bag, update the belief after observing 3 green balls drawn. Answer: 2/7.
Concept and Intuition
Before drawing, any number of green balls from 0 to 6 is equally likely (7 equally likely hypotheses). Observing "all 3 drawn balls are green" is much more likely under hypotheses with more green balls, so Bayes' theorem reweights the prior toward higher k. We want the posterior probability that k=5.
Step-by-Step Solution
- Prior: P(k green balls)=71 for k=0,1,…,6.
- Likelihood of drawing 3 balls, all green, given k green balls out of 6: P(all green∣k)=(36)(3k)=20(3k) (zero for k<3).
- Compute: k=3:(33)=1⇒1/20; k=4:(34)=4⇒4/20; k=5:(35)=10⇒10/20; k=6:(36)=20⇒20/20=1. …
- AP EAPCET 2026Set eng-2026-05-18-FN1 markMCQQ.Two balls are drawn at random from a box containing 4 white, 6 black balls one after the other without replacement. If it is known that second ball drawn is black, then the probability that the first ball drawn is also black is (A) 115 (B) 95 (C) 125 (D) 135
›Reveal solutionSolution
Conditional probability with sampling without replacement, solved with Bayes' theorem; answer is 95.
Concept and Intuition
When balls are drawn one after another without replacement, the marginal probability that any particular draw (say the 2nd) is black equals the overall proportion of black balls, 106 — position doesn't matter for the marginal event by symmetry. To find the conditional probability of the first draw given information about the second, we use Bayes' theorem: we need the joint probability of both events and divide by the marginal probability of the conditioning event.
Step-by-Step Solution
- Total balls: 4 white (W) + 6 black (B) = 10.
- P(2nd is black)=P(1st B, 2nd B)+P(1st W, 2nd B) =106⋅95+104⋅96=9030+9024=9054=53.
- P(1st black and 2nd black)=106⋅95=9030=31. …
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