Q.A bag contains 5 red marbles and 3 black marbles. Three marbles are drawn one by one without replacement. What is the probability that at least one of the three marbles drawn be black, if the first marble is red?
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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). …
Concept: Conditional Probability — we are finding the probability of an event given that a specific condition (first marble is red) has already occurred.
Since the first marble is red, the remaining bag contains 4 red and 3 black marbles (total 7). We now draw two more marbles without replacement.
Step 1: It is easier to find the complement — the probability that none of the next two marbles is black (i.e., both are red).
Step 2: Probability that the second marble is red (given first was red) is 74. After that, probability that the third marble is also red is 63=21. …
Given the first marble is red, the bag holds 4 red and 3 black. The chance the next two are both red is 74⋅63=72, so the probability of at least one black is 1−72=75.
Since the first marble drawn is red, the remaining bag contains
5−1=4 red,3 black,total 7,
and two more marbles are drawn without replacement. "At least one of the three is black" is now the same as "at least one of the next two is black," so use the complement.
1. Both of the next two are red (no black).
- Second marble red: 74.
- Then 3 red remain out of 6, so third marble red: 63=21.
P(both red)=74×21=72.
2. At least one black. …
Method: Conditional Probability with an Updated Sample Space and the "At Least One" Complement
Use this for without-replacement draws where a condition is already known and you want "at least one" of a colour.
Steps
Step 1: Update the composition using the given condition.
Once the first draw is known (e.g. a red is removed), recompute how many of each item remain. All later probabilities are taken from this reduced pool.
Step 2: Recognise "at least one" and complement it.
Directly summing "one, two, …" is long; the complement of "at least one black" is "no black at all" (every remaining draw is red): …
Common Mistakes
Mistake 1: Not updating the bag after the first red is drawn.
Why it's wrong: given the first marble is red, only 4 red and 3 black remain; using the original 5 red overstates the reds. Correct approach: compute later draws from the 4-red, 3-black pool.
Mistake 2: Adding probabilities for "at least one black" case by case over three draws. …
- CA Foundation 2026Set jan-20261 markMCQQ.If in a class, 50% of the student study mathematics and science and 70% of the student study mathematics, then the probability of a student studying science given that he/she is already studying mathematics is (A) 73 (B) 76 (C) 74 (D) 75
›Reveal solutionSolution
Conditional probability P(S∣M)=P(M)P(M∩S).
Step 1 — identify the probabilities
50% study both maths and science, so P(M∩S)=0.5; 70% study maths, so P(M)=0.7.
Step 2 — apply the conditional-probability formula
P(S∣M)=P(M)P(M∩S)=0.70.5=75. …
- CA Foundation 2026Set jan-20261 markMCQQ.If two dice are rolled, then the probability of getting a greater number on the first die than the one on the second, given that the sum should be equal to 7 is (A) 21 (B) 31 (C) 61 (D) 32
›Reveal solutionSolution
Conditional probability on a reduced sample space: P(A∣B)=n(B)n(A∩B).
Step 1 — list the outcomes with sum 7.
(1,6),(2,5),(3,4),(4,3),(5,2),(6,1)⇒n(B)=6.
Step 2 — count first die greater than second, among those.
(4,3),(5,2),(6,1) → 3 outcomes.
Step 3 — conditional probability.
P=63=21. …
- CA Foundation 2023Set jun-20231 markMCQQ.If P(A)=31,P(B)=41,P(A/B)=61, the probability P(B/A) is (A) 81 (B) 41 (C) 83 (D) 21
›Reveal solutionSolution
P(B/A) = P(A∩B)/P(A) = (1/24)/(1/3) = 1/8.
Step 1 — Find the joint probability
P(A∩B)=P(A/B)P(B)=61×41=241
Step 2 — Apply the definition of conditional probability
P(B/A)=P(A)P(A∩B)=1/31/24=243=81
Watch outP(A/B) and P(B/A) are not equal — you must recompute the joint probability first, then divide by P(A), not P(B). …
- CA Foundation 2022Set dec-20221 markMCQQ.If P(A)=31, P(B)=43 and P(A∪B)=1211 then P(AB) is: (A) 61 (B) 94 (C) 21 (D) 81
›Reveal solutionSolution
P(A∩B)=1/6, so P(B|A)=(1/6)/(1/3)=1/2.
Step 1 — Intersection via the addition rule
P(A∩B)=P(A)+P(B)−P(A∪B)=31+43−1211=124+9−11=122=61
Step 2 — Apply the conditional-probability formula
P(AB)=P(A)P(A∩B)=1/31/6=21
Watch outOption (A) 1/6 is just P(A∩B) — you must still divide by P(A) to get the conditional probability. …
- CA Foundation 2021Set dec-20211 markMCQQ.For any two dependent events A and B, P(A)=5/9 and P(B)=6/11 and P(A∩B)=10/33. What are the values of P(A/B) and P(B/A)? (A) 5/9, 6/11 (B) 5/6, 6/11 (C) 1/9, 2/9 (D) 2/9, 4/9
›Reveal solutionSolution
Divide the joint probability by the conditioning event's probability: P(A∣B)=5/9, P(B∣A)=6/11.
Step 1 — Apply the conditional probability formula for P(A∣B)
P(A∣B)=P(B)P(A∩B)=6/1110/33=3310×611=198110=95
Step 2 — Apply it for P(B∣A)
P(B∣A)=P(A)P(A∩B)=5/910/33=3310×59=16590=116
Step 3 — Sanity check
Since P(A)P(B)=(5/9)(6/11)=10/33=P(A∩B), the conditionals collapse to the marginals — consistent with the computed values. …
- CA Foundation 2021Set dec-20211 markMCQQ.In a group of 20 males and 15 females, 12 males and 8 females are service holders. What is the probability that a person selected at random from the group is a service holder given that the selected person is a male? (A) 0.40 (B) 0.60 (C) 0.45 (D) 0.55
›Reveal solutionSolution
Condition on males only: 12 service holders out of 20 males = 0.60.
Step 1 — Identify the reduced sample space
Given the person is male, only the 20 males matter.
Step 2 — Apply the conditional formula
P(service∣male)=total malesmale service holders=2012=0.60
Watch outDo not divide by the full group of 35 — the condition 'given male' shrinks the denominator to 20. …
- JKBOSE Class 12 Annual Regular Examination 2018Set WZ1 markMCQQ.If P(A)=103, P(B)=52 and P(A∪B)=53, then P(B/A)+P(A/B) equals:(a) 1/4(b) 1/3(c) 5/12(d) 7/2
›Reveal solutionSolution
Using P(A∩B)=P(A)+P(B)−P(A∪B) and the conditional-probability definitions, the correctly computed value is 127, which does not equal any of the four listed options.
Given P(A)=103, P(B)=52, P(A∪B)=53.
P(A∩B)=P(A)+P(B)−P(A∪B)=103+104−106=101
P(B/A)=P(A)P(A∩B)=3/101/10=31
P(A/B)=P(B)P(A∩B)=4/101/10=41
P(B/A)+P(A/B)=31+41=124+123=127
This is the value obtained by correctly applying the standard formulas to the numbers as given in the question. It does not match any of the four printed options — (a) 1/4,
(b) 1/3,
(c) 5/12, …
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