Q.A fair die is rolled once. Let E be the event "the number is even" and F be the event "the number is at least 4". Find P(E∣F) and P(F∣E).
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.
[!TLDR] Use P(E∣F)=P(E∩F)/P(F) with E∩F={4,6}. [!ANSWER] P(E∣F)=32 and P(F∣E)=32.
P(E)=63=21, P(F)=63=21, and E∩F={4,6} so P(E∩F)=62=31. Then P(E∣F)=P(F)P(E∩F)=1/21/3=32, and P(F∣E)=P(E)P(E∩F)=1/21/3=32. [!ANSWER] P(E∣F)=32, P(F∣E)=32.
List the outcomes in each event, find E∩F, then divide P(E∩F) by the conditioning event's probability.
Dividing by P(E) instead of P(F) when finding P(E∣F) (mixing up which event is the condition) is the most common slip.
Showing the 12 most recent of 88 on this concept.
- CBSE 2026Set 65/1/11 markMCQQ.Assertion (A): In an experiment of throwing an unbiased die, the probability of getting a prime number given that the number appearing on the die is odd is 32. Reason (R): For any two events A and B, P(A∣B)=P(B)P(A∪B). (A) Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of the Assertion (A). (B) Both Assertion (A) and Reason (R) are true but Reason (R) is not the correct explanation of the Assertion (A). (C) Assertion (A) is true and Reason (R) is false. (D) Assertion (A) is false and Reason (R) is true.
›Reveal solutionSolution
The assertion is true: given the outcome is odd, the probability it is a prime is 32. The reason states the correct conditional probability formula. Since the reason directly justifies the calculation in the assertion, both are true and the reason is the correct explanation.
Concept first — Conditional probability asks: If we already know that event B has occurred, what is the probability that event A also occurs? The sample space shrinks from all possible outcomes to just those in B. The formula P(A∣B)=P(B)P(A∩B) is the precise way to compute this reduced probability.
Here, the die is unbiased, so each face {1,2,3,4,5,6} has probability 61. The assertion involves two events:
- A: the number is prime. On a die, the primes are 2,3,5.
- B: the number is odd. The odd numbers are 1,3,5.
The condition "given that the number is odd" means we restrict attention to B={1,3,5}. Among these three equally likely outcomes, the primes are 3 and 5 — that's two out of three. So the conditional probability is 32.
Now let's verify step by step using the formula in Reason (R).
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Define the events precisely.
A={2,3,5}, B={1,3,5}.
The sample space S={1,2,3,4,5,6}.
-
Compute P(B).
B has 3 outcomes, each with probability 61, so P(B)=63=21.
-
Compute P(A∩B).
A∩B = numbers that are both prime and odd = {3,5}. That's 2 outcomes, so P(A∩B)=62=31.
-
Apply the formula from Reason (R).
P(A∣B)=P(B)P(A∩B)=1/21/3=31×12=32.
This matches the assertion exactly.
Watch outA common mistake is to forget that the condition reduces the sample space. Some students count primes among all six numbers (3 primes) and odd numbers among all six (3 odds), then incorrectly write 33=1 or 63÷63=1. The formula forces you to consider only the overlap, which correctly gives 32.
-
Check the truth of Reason (R).
The formula P(A∣B)=P(B)P(A∩B) is the standard definition of conditional probability (provided P(B)=0). It is always true. So Reason (R) is true.
-
Does Reason (R) correctly explain Assertion (A)?
Yes — the assertion's value 32 is obtained directly by substituting the probabilities into this formula. The reason is not just a true statement; it is the very tool used to verify the assertion.
TipWhen both assertion and reason are true, and the reason is the principle that justifies the assertion, the answer is option (A). If the reason were true but irrelevant to the assertion, it would be option (B).
✓Final answerThe correct option is (A) — Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of the Assertion (A).
- CBSE 2026Set V11 markQ.Choose from [0,3,−1,2,−2,1]. If F is an event of a sample space S then P(S∣F)= ____.
›Reveal solutionSolution
Since S∩F=F, the conditional probability P(S∣F)=1.
By the definition of conditional probability (with P(F)=0),
P(S∣F)=P(F)P(S∩F).
The sample space S contains every outcome, so S∩F=F and P(S∩F)=P(F). Therefore
P(S∣F)=P(F)P(F)=1.
✓Final answer1
- CBSE 2026Set CX1 markMCQQ.If 3P(A)=P(B)=135 and P(A/B)=52, then P(A∪B) will be:(a) 3920(b) 3916(c) 3911(d) 3914
›Reveal solutionSolution
Using P(A∩B)=P(A/B)P(B) and the addition rule gives P(A∪B)=3914 — option (d).
Given: 3P(A)=P(B)=135 and P(A/B)=52.
So P(B)=135 and P(A)=31⋅135=395.
Intersection (multiplication rule):
P(A∩B)=P(A/B)P(B)=52⋅135=132.
Union (addition rule), with common denominator 39:
P(A∪B)=P(A)+P(B)−P(A∩B)=395+3915−396=3914.
✓Final answerOption (d) P(A∪B)=3914.
- CBSE 2026Set A1 markMCQQ.P(A)=137, P(B)=139, P(A∩B)=134⇒P(A/B)=(a) 94(b) 74(c) 1312(d) 61
›Reveal solutionSolution
P(A∣B)=94.
Use the conditional-probability definition:
P(A∣B)=P(B)P(A∩B).
Substitute the given values:
P(A∣B)=139134=134⋅913=94.
✓Final answer(a) 94.
- CBSE 2026Set ANNUAL1 markMCQQ.If P(B)=0.5 and P(A∩B)=0.32, then write the value of P(A∣B).(a) 2315(b) 2516(c) 2716(d) 2316
›Reveal solutionSolution
By the definition of conditional probability, P(A∣B)=P(B)P(A∩B)=2516.
The conditional probability of A given B is defined as
P(A∣B)=P(B)P(A∩B),P(B)eq0
Substituting the given values P(B)=0.5 and P(A∩B)=0.32:
P(A∣B)=0.50.32=0.64=10064=2516
✓Final answerThe correct option is (b) 2516.
- CBSE 2026Set ANNUAL1 markQ.A family has two children. What is the probability that both the children are boys given that at least one of them is a boy?
›Reveal solutionSolution
List the equally likely outcomes for two children, restrict to those with at least one boy, then find the fraction that are both boys.
Sample space ={BB,BG,GB,GG}, each equally likely.
Given at least one boy: reduced sample space ={BB,BG,GB} (3 outcomes).
Of these, both boys occurs only in {BB} (1 outcome).
P(both boys∣at least one boy)=31.
✓Final answerThe probability is 1/3.
- CBSE 2026Set ANNUAL1 markMCQQ.If P(A)=0.8, P(B)=0.5 and P(AB)=0.4 then P(A∩B)=(a) 0.8(b) 0.5(c) 0.32(d) 0.4
›Reveal solutionSolution
Use the multiplication rule of conditional probability: P(A∩B)=P(B∣A)⋅P(A).
Given P(A)=0.8, P(B∣A)=0.4.
P(A∩B)=P(B∣A)⋅P(A)=0.4×0.8=0.32.
(Note: P(B)=0.5 is extra information not needed for this computation.)
✓Final answer(c) 0.32.
- CBSE 2026Set ANNUAL1 markMCQQ.If P(A)=103, P(B)=52 and P(A∪B)=53, then P(B/A) is:(a) 41(b) 31(c) 125(d) 127
›Reveal solutionSolution
Find P(A∩B) from the addition rule, then use the conditional probability formula.
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
✓Final answerOption (b): 31
- CBSE 2026Set ANNUAL1 markQ.A doctor is to visit a patient. From past experience it is known that the probabilities that he will come by train, bus, scooter or by other means of transport are respectively 103,51,101 and 52. The probabilities that he will be late are 41,31 and 121, if he comes by train, bus and scooter respectively, but if he comes by other means of transport, then he will not be late. Probability that he will not be late, when he comes by other means of transport.
›Reveal solutionSolution
The problem statement itself states that if the doctor comes by other means, he will never be late.
Let E1,E2,E3,E4 denote the events that the doctor comes by train, bus, scooter, or other means, with P(E1)=103, P(E2)=51, P(E3)=101, P(E4)=52 (these sum to 1, confirming they form a complete set of cases).
Let L be the event that he is late. We are given P(L∣E1)=41, P(L∣E2)=31, P(L∣E3)=121, and "if he comes by other means, he will not be late", i.e. P(L∣E4)=0.
So P(not late∣E4)=1−P(L∣E4)=1−0=1.
✓Final answerP(not late∣other means)=1
- CBSE 2026Set ANNUAL1 markMCQQ.If P(A) = 1/2, P(B) = 3/8 and P(A∪B) = 27/40 then P(A/B) is equal to:(a) 2/5(b) 8/15(c) 2/3(d) 5/8
›Reveal solutionSolution
First find P(A∩B) using the addition rule, then apply the conditional probability formula P(A/B)=P(B)P(A∩B).
Given P(A)=21, P(B)=83, P(A∪B)=4027.
Using the addition rule P(A∪B)=P(A)+P(B)−P(A∩B):
P(A∩B)=P(A)+P(B)−P(A∪B)=4020+4015−4027=408=51
Now, conditional probability:
P(A/B)=P(B)P(A∩B)=3/81/5=51×38=158
✓Final answerP(A/B)=158 (option b).
- CBSE 2026Set ANNUAL1 markMCQQ.Assertion (A): If P(A) = 0.8, P(B) = 0.5 and P(B/A) = 0.4 then P(A∩B) = 0.32 Reason (R): Conditional Probability of 'B' when event A has occurred is given by P(B/A) = P(A∩B) / P(A)(a) Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of Assertion (A).(b) Both Assertion (A) and Reason (R) are true, but Reason (R) is not the correct explanation of Assertion (A).(c) Assertion (A) is true but Reason (R) is false.(d) Both Assertion (A) and Reason (R) are false.
›Reveal solutionSolution
Applying the conditional-probability formula in R directly to the given numbers reproduces the value claimed in A.
Reason (R): P(B/A)=P(A)P(A∩B) is the standard definition of conditional probability — true.
Checking Assertion (A): Given P(A)=0.8, P(B/A)=0.4. Rearranging R's formula:
P(A∩B)=P(B/A)×P(A)=0.4×0.8=0.32.
This matches A exactly, so A is true, and R is precisely the formula used to derive it.
(Note: P(B)=0.5 is extra information, not needed for this particular computation.)
✓Final answerBoth Assertion (A) and Reason (R) are true, and R is the correct explanation of A. (Option a)
- CBSE 2026Set ANNUAL1 markMCQQ.If P(A)=21 and P(B)=0, then P(A∣B) is(a) 0(b) 21(c) 1(d) Not defined
›Reveal solutionSolution
Conditional probability is defined as P(A∣B)=P(B)P(A∩B), which requires dividing by P(B) — impossible when P(B)=0.
Given P(A)=21, P(B)=0.
By definition:
P(A∣B)=P(B)P(A∩B)
Since P(B)=0, this involves division by zero, which is undefined regardless of the value of P(A∩B) (and note P(A∩B)≤P(B)=0 forces P(A∩B)=0 too, giving the indeterminate 00).
P(A∣B) is not defined.
✓Final answer(d) Not defined
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