Q.If P(A)=137, P(B)=139 and P(A∩B)=134, evaluate P(A∣B).
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).
- If P(A∣B)=P(A), then knowing B tells you nothing about A — the events are independent. That is a special case, not the general rule.
Conditional probability is the foundation of the multiplication theorem, independence, and Bayes' theorem — every "given that" question in this chapter rests on it.
Conditional Probability opens the CBSE Class 12 Probability chapter and is foundational for everything that follows in that unit, including Bayes' theorem and the multiplication rule — making "conditional probability formula class 12 with examples" one of the most searched topics in Class 12 Mathematics. It is equally important for JEE Main and CUET, where conditional probability questions are set almost every year.
Concept: Conditional Probability — the probability of A given B is the ratio of their intersection to the probability of B.
Step 1: Write the formula for conditional probability:
P(A∣B)=P(B)P(A∩B)
Step 2: Substitute the given values:
P(A∣B)=139134
Step 3: Simplify by cancelling 131:
P(A∣B)=94
The value is 94.
Using the definition of conditional probability, P(A∣B)=P(B)P(A∩B). Substituting the given values gives 9/134/13=94.
Conditional probability answers the question: If we know that event B has occurred, how does that change the chance that event A also occurs? The key insight is that knowing B happened restricts the "sample space" to just the outcomes in B. So instead of measuring P(A) against the whole space, we measure P(A∩B) — the part of A that lies inside B — against P(B).
This is exactly the formula:
P(A∣B)=P(B)P(A∩B)
It works because we are renormalising the probability of the overlap by the probability of the new "universe" (B). No extra conditions needed — just plug in the numbers.
-
Identify the given probabilities:
P(A)=137, P(B)=139, P(A∩B)=134.
-
Write the definition of conditional probability:
P(A∣B)=P(B)P(A∩B)
- Substitute the known values:
P(A∣B)=139134
- Simplify the fraction: The 131 cancels in numerator and denominator, leaving
P(A∣B)=94
A common mistake is to use P(A) instead of P(A∩B) in the numerator. Remember: conditional probability only cares about the part of A that overlaps with B — not the whole of A.
Notice that P(A)=137 was not needed at all for this calculation. Sometimes problems give extra information to test whether you know the correct formula.
The value is 94.
Method: Computing a conditional probability from the three basic quantities
Use this direct approach whenever you are handed P(A), P(B) and P(A∩B) and asked for a conditional probability.
Steps
Step 1: Identify the conditioning event — it sets the denominator.
The event written after the vertical bar is the one you are "given," so its probability goes in the denominator. For P(A∣B) the condition is B.
Step 2: Apply the definition.
P(A∣B)=P(B)P(A∩B).
The numerator is always the joint probability P(A∩B) — the overlap — never P(A) on its own.
Step 3: Substitute and simplify; ignore any unused data.
Put the given fractions in and simplify. Questions often supply an extra value (such as P(A)) that is not needed — recognising that it plays no role is part of the skill, not a sign you missed a step.
Common Mistakes
Mistake 1: Putting P(A) in the numerator instead of P(A∩B).
Why it's wrong: conditional probability measures only the part of A lying inside B, which is P(A∩B). Using 9/137/13 gives 97, a wrong answer. Correct approach: always use P(A∣B)=P(B)P(A∩B)=9/134/13=94.
Mistake 2: Trying to use the unneeded value P(A)=137.
Why it's wrong: the formula needs only P(A∩B) and P(B); the extra datum is a distractor. Correct approach: recognise which quantities the formula actually requires and ignore the rest.
Showing the 12 most recent of 45 on this concept.
- 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:
P(A∪B)=126+124−121=129=43.
Step 3 — De Morgan's law.
The event "neither A nor B occurs" is exactly the complement of "A or B occurs":
A′∩B′=(A∪B)′.
Hence
P(A′∩B′)=1−P(A∪B)=1−43=41.
✓Final answerThe correct option is (D) — 1/4.
ANSWER: D
- 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.
First find P(A∣B)=P(B)P(A∩B)=1/21/6=31. Since A and A′ partition the space, P(A∣B)+P(A′∣B)=1, so
P(A′∣B)=1−31=32
Both routes agree. (Note P(A)=31 was not even needed — a useful reminder that a conditional probability given B depends only on how B is split.)
✓Final answerThe correct option is (A) — 32.
ANSWER: A
- 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:
P(A∪Bˉ)=P(A)+P(Bˉ)−P(A∩Bˉ)
We have P(Bˉ)=1−P(B)=1−0.4=0.6.
So P(A∪Bˉ)=0.7+0.6−0.5=0.8.
-
Compute the conditional probability
P(B∣A∪Bˉ)=P(A∪Bˉ)P(A∩B)=0.80.2=0.25.
TipA common mistake is to forget that B∩Bˉ=∅ and try to compute P(B∩(A∪Bˉ)) directly — but the distributive trick saves time and avoids errors.
Watch outDo not confuse P(A∪Bˉ) with P(A)+P(Bˉ) — they are not disjoint because A and Bˉ can overlap (and indeed do, since P(A∩Bˉ)=0.5).
✓Final answerThe correct option is (D).
ANSWER: D
- KCET 2025Set A-11 markMCQQ.If A and B are two events such that A⊂B and P(B)=0, then which of the following is correct? (A) P(A∣B)=P(A)P(B) (B) P(A∣B)<P(A) (C) P(A∣B)≥P(A) (D) P(A)=P(B)
›Reveal solutionSolution
Use A⊂B⇒A∩B=A, then note that dividing P(A) by P(B)≤1 cannot make it smaller.
Step 1 — Simplify the intersection.
If every element of A lies in B, then A∩B=A. Hence
P(A∣B)=P(B)P(A∩B)=P(B)P(A).
Step 2 — Compare with P(A).
Every probability satisfies 0<P(B)≤1 (we are told P(B)=0). Therefore P(B)1≥1, and multiplying the non-negative number P(A) by a factor ≥1 gives
P(A∣B)=P(A)⋅P(B)1≥P(A).
Equality holds exactly when P(B)=1 (or when P(A)=0).
Intuition: conditioning on B throws away all outcomes outside B — but none of A lies outside B. So A's share of the shrunken sample space can only grow.
Step 3 — Eliminate.
- (A) P(A∣B)=P(B)/P(A) — wrong; the ratio is upside down (and can exceed 1).
- (B) P(A∣B)<P(A) — the inequality points the wrong way.
- (D) P(A)=P(B) — not implied; A can be a strictly smaller subset, e.g. rolling a die with A={2}, B={2,4,6}: P(A)=1/6, P(B)=1/2, and P(A∣B)=1/3≥1/6. ✓ consistent only with (C).
✓Final answerThe correct option is (C) — P(A∣B)≥P(A).
ANSWER: C
- 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.
Watch outA common mistake is to confuse P(A−B) with P(Bc) or to think P(A−B)=P(A)−P(B). Remember: A−B is only the part of A that excludes B, not the whole complement of B.
TipVisualize a Venn diagram: A is a circle split into the B overlap and the rest. P(A−B) is the “crescent” of A outside B. Subtracting that from P(A) gives the overlap directly.
✓Final answerThe correct option is (A).
ANSWER: A
- 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.
Common denominator 12: 123+122−121=124=31.
So P(P∩Q)=1−31=32.
- Compute the desired conditional probability.
P(P∣Q)=P(Q)P(P∩Q)=6532=32⋅56=1512=54.
Watch outA common mistake is to assume P(P∣Q) and P(Q∣P) are reciprocals or that P(P∩Q) can be found by multiplying P(P) and P(Q) directly — that only works for independent events, which is not the case here.
TipYou can also solve this by constructing a 2×2 probability table. From P(P)=41 and P(P∩Q)=121, fill in the rest systematically. The final answer is the same.
✓Final answerThe correct option is (A).
ANSWER: A
- 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.
LCM of 15 and 35 is 105:
152=10514,356=10518,
P(F)=10514+10518=10532.
Step 5 — Apply Bayes.
P(B∣F)=32/10518/105=3218=169.
(Check: P(A∣F)=3214=167, and 169+167=1 ✓. Note option (A) 167 is the trap — it is the probability for temple A.)
✓Final answerThe correct option is (D) — 169.
ANSWER: D
- 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).
P(A)=54−53+103=51+103=102+103=105=21.
Consistency check. With P(A)=21, P(B)=53, P(A∩B)=103: note P(A)P(B)=21⋅53=103=P(A∩B), so A and B are independent — entirely consistent with P(A/B)=21=P(A). And P(A∪B)=21+53−103=105+6−3=108=54. ✓
✓Final answerThe correct option is (B) — 21.
ANSWER: B
- 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.
Equality of probabilities does not force equality of sets. Example: toss a fair coin twice; let A = "first toss is head", B = "second toss is head". Then P(A)=P(B)=1/2, P(A∩B)=1/4=0, and indeed P(A∣B)=P(B∣A)=1/2 — yet A=B and neither is a subset of the other. So (A) and (B) are not implied. (C) contradicts the given non-mutual-exclusivity.
✓Final answerThe correct option is (D) — P(A)=P(B).
ANSWER: D
- 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)
P(A′∩B)=P(B)−P(A∩B)=31−61=61(C true)
Option (D) "A and B are independent" is true. Therefore the statement that is not true is (A) "A and B are not independent".
✓Final answerThe statement that is not true is "A and B are not independent" — option (A).
- COMEDK 2026Set 2026-M1 markMCQQ.Advika chooses one of three scarves every morning: Red, Blue, or Green. The probability she chooses Red is 20%. The probability she chooses Blue is twice the probability of choosing Red. On the remaining days she wears a Green scarf. Once a scarf is chosen, she decides whether to wear a Hat (H) and Sunglasses (S). These choices are independent of each other but depend on the scarf colour: Scarf colour Red Blue Green P(H)0.50.40.1P(S)0.80.50.5 Advika is spotted outdoors wearing both a Hat and Sunglasses. What is the probability that she is wearing the Red scarf? (A) 31313 (B) 218 (C) 94 (D) 138
›Reveal solutionSolution
Bayes' theorem on scarf colour given that both a hat and sunglasses are worn. Priors P(R)=0.2, P(B)=0.4, P(G)=0.4; likelihoods P(H∩S∣colour)=P(H)P(S). The posterior P(R∣H∩S)=94 — option (C).
Concept. Hat and sunglasses are independent given the scarf, so P(H∩S∣colour)=P(H∣colour)⋅P(S∣colour). Bayes' theorem then reverses the conditioning to give the probability of the scarf colour from the observed accessories.
Step 1 — Priors.
P(R)=20%=0.2,P(B)=2P(R)=0.4,P(G)=1−0.2−0.4=0.4.
Step 2 — Likelihood of wearing both accessories for each colour.
P(H∩S∣R)=0.5×0.8=0.40,
P(H∩S∣B)=0.4×0.5=0.20,
P(H∩S∣G)=0.1×0.5=0.05.
Step 3 — Total probability of both accessories (denominator).
P(H∩S)=(0.2)(0.40)+(0.4)(0.20)+(0.4)(0.05)=0.08+0.08+0.02=0.18.
Step 4 — Posterior for Red.
P(R∣H∩S)=P(H∩S)P(R)P(H∩S∣R)=0.180.08=188=94.
✓Final answerP(Red∣H∩S)=94 — option (C).
ANSWER: C
- 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.
Step 4: P(A' U B) = 1 - P((A' U B)') = 1 - P(A ^ B') [De Morgan]
P(A ^ B') = P(A) - P(A ^ B) = 1/2 - 3/10 = 1/5.
So P(A' U B) = 1 - 1/5 = 4/5.
Step 5: sum = 1/5 + 4/5 = 1.
✓Final answerThe correct option is (C) — 1
ANSWER: C
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