Q.A manufacturer has three machine operators A, B and C. The first operator A produces 1% defective items, where as the other two operators B and C produce 5% and 7% defective items respectively. A is on the job for 50% of the time, B is on the job for 30% of the time and C is on the job for 20% of the time. A defective item is produced, what is the probability that it was produced by A?
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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 (Bayes' Theorem)
We want P(A∣D), the probability that operator A produced the item given it is defective.
Step 1 – Prior probabilities
P(A)=0.50, P(B)=0.30, P(C)=0.20.
Step 2 – Likelihoods (defect rates)
P(D∣A)=0.01, P(D∣B)=0.05, P(D∣C)=0.07.
Step 3 – Total probability of a defect
P(D)=P(A)P(D∣A)+P(B)P(D∣B)+P(C)P(D∣C) …
By Bayes' theorem, P(A∣defective)=345≈0.147.
Let A,B,C be the events that an item was made by operator A, B, C, and D that it is defective.
P(A)=0.5, P(B)=0.3, P(C)=0.2,P(D∣A)=0.01, P(D∣B)=0.05, P(D∣C)=0.07.
Total probability of a defective item:
P(D)=(0.5)(0.01)+(0.3)(0.05)+(0.2)(0.07)=0.005+0.015+0.014=0.034.
Bayes' theorem: …
Method: Bayes' theorem with a several-part partition
Use this for "which source produced it?" problems: an item comes from one of several sources with known proportions, each source has a known defect (or success) rate, and you must find the probability a defective item came from a specific source.
Steps
Step 1: Set up the partition and its prior probabilities.
The sources (operators, machines, bags) must be mutually exclusive and exhaustive. Their proportions of the workload are the priors P(A),P(B),P(C),… and should sum to 1.
Step 2: Write each conditional likelihood.
For every source, note P(D∣source) — here the defect rate for that source. …
Common Mistakes
Mistake 1: Forgetting to weight each defect rate by the operator's share of time.
Why it's wrong: operator A runs the machine 50% of the time, so their contribution to defects is 0.50×0.01, not just 0.01. Correct approach: multiply each defect rate by its prior before comparing or summing.
Mistake 2: Dividing by only A's contribution instead of the total defect probability. …
- 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. …
- AHSEC Higher Secondary (HS) Final Examination 2026Set ANNUAL1 markMCQQ.If A and B are two events such that A⊂B and P(B)=0, then which of the following is correct?(i) P(A∣B)=P(A)P(B)(ii) P(A∣B)<P(A)(iii) P(A∣B)≥P(A)(iv) None of the above
›Reveal solutionSolution
A⊂B⇒A∩B=A⇒P(A∣B)=P(B)P(A)≥P(A) — option (iii).
By definition P(A∣B)=P(B)P(A∩B).
Because A⊂B, we have A∩B=A, so
P(A∣B)=P(B)P(A).
…
- 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. …
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