Q.Let A and B be two events such that P(A)=83, P(B)=85 and P(A∪B)=43. Then P(A∣B)⋅P(A′∣B) is equal to
(A) 52
(B) 83
(C) 203
(D) 256
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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 given P(A)=83, P(B)=85, and P(A∪B)=43.
Step 1: Find P(A∩B)
Using the addition rule:
P(A∪B)=P(A)+P(B)−P(A∩B)
43=83+85−P(A∩B)
43=1−P(A∩B)
So P(A∩B)=1−43=41.
Step 2: Compute P(A∣B) and P(A′∣B)
P(A∣B)=P(B)P(A∩B)=5/81/4=41⋅58=52. …
The key idea is to use the definition of conditional probability and the complement rule. After finding P(A∩B)=41, we compute P(A∣B)=52 and P(A′∣B)=53, so their product is 256, which is option (D).
We start with the given probabilities:
P(A)=83, P(B)=85, and P(A∪B)=43.
The problem asks for P(A∣B)⋅P(A′∣B). This is a product of two conditional probabilities under the same condition B. The intuition: once we know B has occurred, the probability of A and its complement A′ must add to 1. So their product is maximized when they are balanced — but we need the exact numbers.
Step 1: Find P(A∩B) using the addition rule.
The formula for the union of two events is:
P(A∪B)=P(A)+P(B)−P(A∩B)
Substitute the known values:
43=83+85−P(A∩B)
43=1−P(A∩B)
So:
P(A∩B)=1−43=41
A common mistake is to forget that P(A∪B) cannot exceed 1, and here it is less than P(A)+P(B), confirming the events are not mutually exclusive. Always check that P(A∩B) comes out positive.
Step 2: Compute P(A∣B).
By definition:
P(A∣B)=P(B)P(A∩B)=5/81/4=41×58=52
Step 3: Compute P(A′∣B). …
Method: Complementary conditionals under a fixed condition
Use this when a product or sum mixes P(A∣B) and P(A′∣B) under the same condition B.
Steps
Step 1: Recover the overlap and the first conditional.
Get P(A∩B) from the addition rule (or a given conditional), then
P(A∣B)=P(B)P(A∩B).
Step 2: Use the fixed-condition complement rule.
Given B, the outcomes A and A′ partition the reduced sample space, so
P(A′∣B)=1−P(A∣B). …
Common Mistakes
Mistake 1: Computing P(A′∣B) from scratch instead of using 1−P(A∣B).
Why it's wrong: not a fatal error, but it wastes time and invites slips; under the same condition B, the events A and A′ partition the reduced space. Correct approach: P(A′∣B)=1−P(A∣B).
Mistake 2: Forgetting to recover P(A∩B) from the addition rule. …
Showing the 12 most recent of 45 on this concept.
- KCET 2021Set A-11 markMCQQ.Given that A and B are two events such that P(B)=53, P(A/B)=21 and P(A∪B)=54, then P(A)= (A) 103 (B) 21 (C) 51 (D) 53
›Reveal solutionSolution
Turn the conditional probability into P(A∩B), then substitute into the addition theorem and solve for P(A).
Step 1 — Extract P(A∩B) from the conditional probability.
By definition,
P(A/B)=P(B)P(A∩B)(P(B)=0).
Rearranging (the multiplication theorem):
P(A∩B)=P(A/B)⋅P(B)=21×53=103.
This is the key move — the conditional probability is not directly usable in the union formula, but P(A∩B) is.
Step 2 — Apply the addition theorem.
P(A∪B)=P(A)+P(B)−P(A∩B).
The intersection is subtracted because the elements common to A and B would otherwise be counted twice.
Step 3 — Substitute the known values.
54=P(A)+53−103.
Step 4 — Solve for P(A). …
- COMEDK 2025Set 2025-A1 markMCQQ.If for two events A and B,P(A−B)=51 and P(A)=53 then P(B/A)= (A) 32 (B) 21 (C) 53 (D) 52
›Reveal solutionSolution
The key is to interpret P(A−B) as P(A∩Bc) and use the definition of conditional probability. The result is P(B/A)=32, so option (A) is correct.
We are asked for P(B/A), the probability of B given A. The definition is
P(B/A)=P(A)P(A∩B).
We know P(A)=53, so we need P(A∩B). The given P(A−B)=51 is the key: A−B means “A and not B,” i.e., A∩Bc.
- Relate P(A−B) to P(A∩B) Since A is the union of the disjoint parts “A and B” and “A and not B,” we have
P(A)=P(A∩B)+P(A∩Bc).
Here P(A∩Bc)=P(A−B)=51 and P(A)=53.
- Solve for P(A∩B)
53=P(A∩B)+51⇒P(A∩B)=53−51=52.
- Apply the conditional probability formula P(B/A)=P(A)P(A∩B)=3/52/5=32. …
- KCET 2022Set C-41 markMCQQ.If A and B are two events such that P(A)=21, P(B)=31 and P(A∣B)=41, then P(A′∩B′) is (A) 3/16 (B) 1/12 (C) 3/4 (D) 1/4
›Reveal solutionSolution
Get P(A∩B) from the conditional probability, use the addition rule for P(A∪B), then apply De Morgan: P(A′∩B′)=1−P(A∪B).
Step 1 — Recover the joint probability from the conditional.
Conditional probability is defined by P(A∣B)=P(B)P(A∩B) — it re-scales the probability of A to the reduced sample space B. Rearranging gives the multiplication rule:
P(A∩B)=P(A∣B)P(B)=41×31=121.
Step 2 — Addition rule for the union.
P(A∪B)=P(A)+P(B)−P(A∩B)=21+31−121.
Taking LCM 12: …
- COMEDK 2025Set 2025-E1 markMCQQ.If A and B are two events such that P(Aˉ)=0.3,P(B)=0.4,P(A∩Bˉ)=0.5, then find the value of P(B/A∪Bˉ) (A) 0.33 (B) 0.7 (C) 0.8 (D) 0.25
›Reveal solutionSolution
The problem asks for a conditional probability P(B∣A∪Bˉ). Using the definition of conditional probability and the given probabilities, we compute P(B∩(A∪Bˉ)) and P(A∪Bˉ), then divide. The final value is 0.25, so the correct option is (D).
We are given:
- P(Aˉ)=0.3, so P(A)=1−0.3=0.7.
- P(B)=0.4.
- P(A∩Bˉ)=0.5.
We need P(B∣A∪Bˉ), which is the probability that B occurs given that A or Bˉ (or both) occurs.
Concept and intuition:
Conditional probability P(X∣Y)=P(Y)P(X∩Y). Here X=B and Y=A∪Bˉ. So we need the probability that both B and (A∪Bˉ) happen, divided by the probability that A∪Bˉ happens. The key is to simplify the intersection B∩(A∪Bˉ) using set algebra — it often collapses to something simpler.
-
Simplify the numerator P(B∩(A∪Bˉ))
Using the distributive law:
B∩(A∪Bˉ)=(B∩A)∪(B∩Bˉ)
But B∩Bˉ=∅, so this is just B∩A.
Hence P(B∩(A∪Bˉ))=P(A∩B).
-
Find P(A∩B)
We know P(A)=0.7 and P(A∩Bˉ)=0.5.
Since A=(A∩B)∪(A∩Bˉ) and these are disjoint,
P(A)=P(A∩B)+P(A∩Bˉ)
⇒0.7=P(A∩B)+0.5
⇒P(A∩B)=0.2.
-
Find the denominator P(A∪Bˉ)
Use the inclusion-exclusion principle: …
- COMEDK 2023Set 2023-E1 markMCQQ.
[!FORMULA] If P(B)=53P(A/B)=21 and P(A∪B)=54 then P(A∪B)′+P(A′∪B)=
(A) 54 (B) 21 (C) 1 (D) 51›Reveal solutionSolution
Step 5: sum = 1/5 + 4/5 = 1.
Concept: conditional probability, addition theorem, complements, De Morgan.
Given P(B) = 3/5, P(A|B) = 1/2, P(A U B) = 4/5.
Step 1: P(A ^ B) = P(A|B) P(B) = (1/2)(3/5) = 3/10.
Step 2: from P(A U B) = P(A) + P(B) - P(A ^ B),
P(A) = 4/5 - 3/5 + 3/10 = 1/5 + 3/10 = 1/2.
Step 3: P((A U B)') = 1 - P(A U B) = 1 - 4/5 = 1/5. …
- KCET 2020Set A-11 markMCQQ.If A and B are two events such that P(A)=31, P(B)=21 and P(A∩B)=61, then P(A′/B) is (A) 32 (B) 31 (C) 21 (D) 121
›Reveal solutionSolution
Use P(A′∣B)=1−P(A∣B) (equivalently P(B)P(B)−P(A∩B)), which gives 32.
Step 1 — The definition of conditional probability.
For P(B)>0,
P(A′∣B)=P(B)P(A′∩B)
Conditioning on B means we restrict the sample space to B and ask what fraction of B lies outside A.
Step 2 — Split B into the part inside A and the part outside A.
The events A∩B and A′∩B are disjoint and their union is exactly B:
P(B)=P(A∩B)+P(A′∩B)
⇒P(A′∩B)=P(B)−P(A∩B)=21−61=63−1=62=31
Step 3 — Divide by P(B).
P(A′∣B)=P(B)P(A′∩B)=2131=31×12=32
Step 4 — Cross-check with the complement rule. …
- COMEDK 2024Set 2024-A1 markMCQQ.P and Q are considering to apply for a job. The probability that P applies for the job is 41. The probability that P applies for the job given that Q applies for the job is 21, and the probability that Q applies for the job given that P applies for the job is 31. Then the probability that P does not apply for the job given that Q does not apply for the job is (A) 54 (B) 87 (C) 65 (D) 1211
›Reveal solutionSolution
We are given conditional probabilities and need to find P(P∣Q). Using the definitions of conditional probability and the law of total probability, we compute P(Q) and P(Q), then apply Bayes' theorem to get 54, which corresponds to option (A).
Concept and intuition:
This is a classic problem of working backwards from conditional probabilities to find a joint probability table. We know P(P), P(P∣Q), and P(Q∣P). From these, we can find P(P∩Q) in two ways, which lets us solve for P(Q). Then we can compute the desired conditional probability P(P∣Q) using the complement rule and the definition of conditional probability.
Step-by-step solution:
- Write down what is given. Let P = event that P applies, Q = event that Q applies. We have:
P(P)=41,P(P∣Q)=21,P(Q∣P)=31.
- Use the definition of conditional probability to express P(P∩Q) in two ways. From P(P∣Q)=P(Q)P(P∩Q), we get
P(P∩Q)=P(P∣Q)⋅P(Q)=21P(Q).
From P(Q∣P)=P(P)P(P∩Q), we get
P(P∩Q)=P(Q∣P)⋅P(P)=31⋅41=121.
- Equate the two expressions for P(P∩Q) to find P(Q).
21P(Q)=121⇒P(Q)=61.
- Find P(Q) and P(P∩Q).
P(Q)=1−P(Q)=1−61=65.
Also, P(P∩Q)=P(P)−P(P∩Q)=41−121=123−121=122=61.
- Find P(P∩Q). Since P∩Q is the complement of P∪Q, we can use:
P(P∩Q)=1−P(P∪Q).
First, P(P∪Q)=P(P)+P(Q)−P(P∩Q)=41+61−121. …
- COMEDK 2024Set 2024-E1 markMCQQ.Let A and B be two events such that P(A/B)=21 and P(B/A)=31 and P(A∩B)=61 then, which one of the following is not true? (A) A and B are not independent (B) P(A∪B)=32 (C) P(A′∩B)=61 (D) A and B are independent
›Reveal solutionSolution
P(A)=21, P(B)=31, and P(A)P(B)=61=P(A∩B), so A,B ARE independent; the false statement is that they are not independent.
From P(A∩B)=P(A∣B)P(B):
61=21P(B)⟹P(B)=31
From P(A∩B)=P(B∣A)P(A):
61=31P(A)⟹P(A)=21
Independence test:
P(A)P(B)=21⋅31=61=P(A∩B)
So A and B are independent. Checking the other options:
P(A∪B)=21+31−61=32(B true) …
- KCET 2020Set A-11 markMCQQ.The probability of solving a problem by three persons A, B and C independently is 21, 41 and 31 respectively. Then the probability of the problem is solved by any two of them is (A) 121 (B) 41 (C) 241 (D) 81
›Reveal solutionSolution
The problem asks for the probability that exactly two of the three persons solve it. We compute the sum of probabilities for each pair solving while the third fails, giving 81.
The key idea: "solved by any two of them" means exactly two solve it, not at least two. The third person must fail. Since A, B, and C work independently, we multiply their individual probabilities for each specific outcome and then add the three possible cases.
A common mistake is to include the case where all three solve it. That would be "at least two", not "any two". The phrase "any two" in probability problems almost always means exactly two.
Let’s denote:
- P(A)=21, so P(A fails)=1−21=21
- P(B)=41, so P(B fails)=1−41=43
- P(C)=31, so P(C fails)=1−31=32
We want exactly two successes. There are three mutually exclusive ways this happens:
-
A and B solve, C fails
Probability = P(A)×P(B)×P(C fails)
=21×41×32=242=121
-
A and C solve, B fails
Probability = P(A)×P(C)×P(B fails)
=21×31×43=243=81
-
B and C solve, A fails
Probability = P(B)×P(C)×P(A fails) …
- COMEDK 2023Set 2023-E1 markMCQQ.A die is thrown twice and the sum of numbers appearing is observed to be 8 . What is the conditional probability that the number 5 has appeared atleast once? (A) 365 (B) 52 (C) 181 (D) 31
›Reveal solutionSolution
Given the sum is 8, the sample space is the 5 ordered pairs summing to 8; two of them include a 5, giving probability 52.
The ordered outcomes with sum 8 are
(2,6),(3,5),(4,4),(5,3),(6,2)(5 outcomes). …
- KCET 2025Set A-11 markMCQQ.If A and B are two non-mutually exclusive events such that P(A∣B)=P(B∣A), then (A) A⊂B but A=B (B) A=B (C) A∩B=ϕ (D) P(A)=P(B)
›Reveal solutionSolution
Write both conditional probabilities with the same numerator P(A∩B), cancel it (legal because the events are not mutually exclusive), and the denominators must be equal.
Step 1 — Definition of conditional probability.
P(A∣B)=P(B)P(A∩B),P(B∣A)=P(A)P(B∩A).
Note A∩B=B∩A, so the two fractions share the same numerator.
Step 2 — Impose the given condition.
P(B)P(A∩B)=P(A)P(A∩B).
Step 3 — Cancel — and see why we are allowed to.
The events are non-mutually-exclusive, i.e. A∩B=ϕ and P(A∩B)=0. (This hypothesis is exactly what makes the cancellation valid — if P(A∩B) were 0, both sides would be 0 for any P(A),P(B) and nothing would follow.) Dividing both sides by P(A∩B):
P(B)1=P(A)1⟹P(A)=P(B).
Step 4 — Why the other options are not forced. …
- KCET 2025Set A-11 markMCQQ.Meera visits only one of the two temples A and B in her locality. Probability that she visits temple A is 52. If she visits temple A, 31 is the probability that she meets her friend, whereas it is 72 if she visits temple B. Meera met her friend at one of the two temples. The probability that she met her at temple B is (A) 167 (B) 165 (C) 163 (D) 169
›Reveal solutionSolution
The friend has already been met (the effect); we want the probability of the cause (temple B) — that reversal of conditioning is exactly Bayes' theorem.
Step 1 — Name the events.
Let A = "Meera visits temple A", B = "Meera visits temple B", F = "she meets her friend".
She visits only one of the two temples, so A and B are mutually exclusive and exhaustive:
P(A)=52⟹P(B)=1−52=53.
Given: P(F∣A)=31, P(F∣B)=72.
Step 2 — Why Bayes.
We are told the outcome (F happened) and asked for the probability of a cause (B). Bayes' theorem inverts the conditioning:
P(B∣F)=P(A)P(F∣A)+P(B)P(F∣B)P(B)P(F∣B).
The denominator is P(F) by the law of total probability — the friend can be met on either branch.
Step 3 — Compute the two branch probabilities.
P(A∩F)=52×31=152,P(B∩F)=53×72=356.
Step 4 — Total probability of meeting the friend. …
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