Q.If A and B are two events such that P(A)=41, P(B)=21 and P(A∩B)=81, find P (not A and not B).
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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: Complement of a union (De Morgan's law) / Independence check
We want P(not A and not B)=P(A′∩B′). By De Morgan's law, A′∩B′=(A∪B)′, so P(A′∩B′)=1−P(A∪B).
Step 1: Addition rule: P(A∪B)=P(A)+P(B)−P(A∩B)=41+21−81=82+84−81=85.
Step 2: P(A′∩B′)=1−85=83. …
"Not A and not B" is P(A′∩B′)=1−P(A∪B). With P(A∪B)=41+21−81=85, the answer is 1−85=83. (A and B turn out to be independent, so P(A′)P(B′)=43⋅21=83 gives the same value.)
The phrase "not A and not B" means both events fail to occur — the complement of A and the complement of B happen together. In set notation this is A′∩B′.
Step 1 — Turn it into a union using De Morgan's law.
The complement of "both fail to occur" is "at least one occurs", which is exactly A∪B. De Morgan's law states A′∩B′=(A∪B)′, so:
P(A′∩B′)=1−P(A∪B)
Step 2 — Find P(A∪B) with the addition rule.
For any two events,
P(A∪B)=P(A)+P(B)−P(A∩B)
Substitute the given values P(A)=41, P(B)=21, P(A∩B)=81:
P(A∪B)=41+21−81
- Convert to eighths: 41=82, 21=84.
- Add: 82+84=86.
- Subtract: 86−81=85.
So P(A∪B)=85.
Step 3 — Get the required probability. …
Method: Probability of "neither" via De Morgan and the addition rule
Use this whenever a question asks for the chance that both events fail — "neither A nor B", "not A and not B", P(A′∩B′) — given P(A), P(B) and the overlap.
Steps
Step 1: Rewrite "neither" as the complement of a union.
By De Morgan's law, both failing is the same as "at least one occurring" not happening:
P(A′∩B′)=P((A∪B)′)=1−P(A∪B).
This is the key move — a direct product P(A′)P(B′) is only valid under independence, which you should not assume.
Step 2: Find P(A∪B) with the general addition rule. …
Common Mistakes
Mistake 1: Reading "not A and not B" as 1−P(A)−P(B).
Why it's wrong: that drops the overlap correction. Correct approach: use De Morgan, A′∩B′=(A∪B)′, so P(A′∩B′)=1−P(A∪B) with P(A∪B)=P(A)+P(B)−P(A∩B)=85, giving 83.
Mistake 2: Applying De Morgan the wrong way, e.g. A′∩B′=(A∩B)′. …
Showing the 12 most recent of 69 on this concept.
- AP EAPCET 2021Set eng-2021-08-25-AN1 markMCQQ.Given P(A)=0.5,P(B)=0.4,P(A∩B)=0.3 then P(A′/B′) is equal to (A) 31 (B) 21 (C) 32 (D) 43
›Reveal solutionSolution
Using De Morgan's law A′∩B′=(A∪B)′ and the conditional probability formula gives P(A′∣B′)=32.
Concept and Intuition
P(A′∣B′) asks: given we're outside B, what's the chance we're also outside A? The key trick is that A′∩B′=(A∪B)′ (De Morgan), which is easy to compute from P(A∪B).
Step-by-Step Solution
- P(A∪B)=P(A)+P(B)−P(A∩B)=0.5+0.4−0.3=0.6.
- P(A′∩B′)=P((A∪B)′)=1−P(A∪B)=1−0.6=0.4.
- P(B′)=1−P(B)=1−0.4=0.6. …
- AP EAPCET 2024Set eng-2024-05-23-FN1 markMCQQ.It is given that in a random experiment events A and B are such that P(A)=41, P(A∣B)=21 and P(B∣A)=32 then P(B)= (A) 31 (B) 32 (C) 21 (D) 61
›Reveal solutionSolution
Using P(B∣A) to find P(A∩B), then dividing by P(A∣B), gives P(B)=31.
Concept and Intuition
The conditional probability definitions P(A∣B)=P(B)P(A∩B) and P(B∣A)=P(A)P(A∩B) share the common quantity P(A∩B) — computing it from one equation lets us solve the other for the unknown probability.
Step-by-Step Solution
- From P(B∣A)=P(A)P(A∩B)=32, and P(A)=41: P(A∩B)=32×41=61.
- From P(A∣B)=P(B)P(A∩B)=21: P(B)=P(A∣B)P(A∩B)=1/21/6=31.
Common Mistakes …
- AP EAPCET 2022Set eng-2022-07-05-FN1 markMCQQ.If A and B are two events such that P(B)=0 and P(B)=1, then P(Aˉ∣Bˉ) is (A) 1−P(A∣B) (B) 1−P(Aˉ∣B) (C) P(Bˉ)1−P(A∪B) (D) P(Bˉ)P(Aˉ)
›Reveal solutionSolution
Directly apply the definition of conditional probability together with De Morgan's law; the answer is P(Bˉ)1−P(A∪B).
Concept and Intuition
Conditional probability is defined as P(X∣Y)=P(Y)P(X∩Y). Here X=Aˉ, Y=Bˉ. By De Morgan's law, Aˉ∩Bˉ=A∪B, so its probability is 1−P(A∪B).
Step-by-Step Solution
- P(Aˉ∣Bˉ)=P(Bˉ)P(Aˉ∩Bˉ).
- Aˉ∩Bˉ=A∪B (De Morgan).
- So P(Aˉ∩Bˉ)=1−P(A∪B). …
- AP EAPCET 2022Set eng-2022-07-06-FN1 markMCQQ.Two persons P and Q are considering to apply for a job. The probability that P applies for the job is 1/4, the probability that P applies for the job given that Q applies for the job is 1/2, and the probability that Q applies for the job given that P applies for the job is 1/3. Then the probability that P does not apply for the job given that Q does not apply for the job is (A) 4/5 (B) 5/6 (C) 7/8 (D) 11/12
›Reveal solutionSolution
Chain the given conditional probabilities to find P(Q) and P(P∩Q), then use the complement rule — the answer is (A) 4/5.
Concept and Intuition
Conditional probability definitions let us cross-multiply to recover the joint probability P(P∩Q) from either conditional. Once P(P),P(Q),P(P∩Q) are all known, De Morgan's law converts "neither event" into the complement of the union.
Step-by-Step Solution
- Given: P(P)=41, P(P∣Q)=21, P(Q∣P)=31.
- P(P∩Q)=P(Q∣P)⋅P(P)=31×41=121.
- Also P(P∩Q)=P(P∣Q)⋅P(Q)⇒121=21⋅P(Q)⇒P(Q)=61.
- P(P∪Q)=P(P)+P(Q)−P(P∩Q)=41+61−121=123+122−121=124=31.
- By De Morgan's law, "neither P nor Q applies" is the complement of P∪Q: P(P∩Q)=1−31=32.
- P(Q)=1−P(Q)=1−61=65. …
- AP EAPCET 2021Set eng-2021-08-24-FN1 markMCQQ.If A and B are mutually exclusive events with P(A)=41 and P(B)=73. Then what is the value of P(A/A∪B)= (A) 197 (B) 1912 (C) 1906 (D) 1913
›Reveal solutionSolution
Mutually exclusive events make P(A∪B) a simple sum, and since A is entirely contained in A∪B, the conditional probability reduces to P(A)/P(A∪B).
Concept and Intuition
For mutually exclusive A,B: P(A∩B)=0, so P(A∪B)=P(A)+P(B). Also A∩(A∪B)=A always, so P(A∣A∪B)=P(A∪B)P(A∩(A∪B))=P(A∪B)P(A).
Step-by-Step Solution
- P(A∪B)=P(A)+P(B)=41+73.
- Common denominator 28: 287+2812=2819. …
- AP EAPCET 2025Set eng-2025-05-26-FN1 markMCQQ.If two events A and B are such that P(Aˉ)=0.3, P(B)=0.4 and P(A∩Bˉ)=0.5, then P(B/(A∪Bˉ))= (A) 0.25 (B) 0.6 (C) 0.45 (D) 0.8
›Reveal solutionSolution
This tests careful set manipulation of conditional probability with a compound conditioning event A∪Bˉ. Answer: 0.25.
Concept and Intuition
Conditional probability P(B∣E)=P(E)P(B∩E) works exactly the same way when E is a compound event like A∪Bˉ — we just need to correctly compute P(E) and P(B∩E) using set algebra (distributing intersection over union, and using the fact that B and Bˉ are disjoint).
Step-by-Step Solution
- From P(Aˉ)=0.3, get P(A)=1−0.3=0.7.
- P(A∩Bˉ)=0.5 is given directly, so P(A∩B)=P(A)−P(A∩Bˉ)=0.7−0.5=0.2.
- Compute P(A∪Bˉ) using inclusion-exclusion: P(A∪Bˉ)=P(A)+P(Bˉ)−P(A∩Bˉ). Here P(Bˉ)=1−0.4=0.6, so P(A∪Bˉ)=0.7+0.6−0.5=0.8. …
- AP EAPCET 2023Set eng-2023-05-16-AN1 markMCQQ.Two dice are rolled. If A denote the event that the same number shows on each die and B denote the event that the sum of the numbers on both dice is greater than 7, then P(A∣B) and P(B∣A) respectively are (A) 52,41 (B) 51,21 (C) 51,41 (D) 21,53
›Reveal solutionSolution
Counting the 36 equally likely dice outcomes directly gives P(A∣B)=51 and P(B∣A)=21.
Concept and Intuition
With two fair dice there are 36 equally likely outcomes, so every probability here reduces to simple counting: enumerate the outcomes in A, in B, and in A∩B, then apply the conditional probability formula P(X∣Y)=P(Y)P(X∩Y) directly as a ratio of counts.
Step-by-Step Solution
- A = "same number on each die": outcomes (1,1),(2,2),(3,3),(4,4),(5,5),(6,6) — 6 outcomes, so P(A)=366.
- B = "sum >7", i.e. sum ∈{8,9,10,11,12}. Counting pairs per sum: sum 8 has 5 pairs, 9 has 4, 10 has 3, 11 has 2, 12 has 1 — total 5+4+3+2+1=15 outcomes, so P(B)=3615.
- A∩B: doubles with sum >7 — check each double: (4,4) sum 8 ✓, (5,5) sum 10 ✓, (6,6) sum 12 ✓; (1,1),(2,2),(3,3) have sums 2,4,6, all ≤7 — excluded. So A∩B has 3 outcomes, P(A∩B)=363. …
- AP EAPCET 2023Set eng-2023-05-18-AN1 markMCQQ.If A,B are any two events of a random experiment and P(B)=1, then P(A∣Bc)= (A) 1−P(B)P(A)+P(A∩B) (B) 1−P(B)P(A)−P(A∩B) (C) 1+P(B)P(A)+P(A∩B) (D) 1+P(B)P(A)
›Reveal solutionSolution
Direct application of the conditional-probability definition to the complement event gives P(A∣Bc)=1−P(B)P(A)−P(A∩B).
Concept and Intuition
A∩Bc is exactly the part of A that does not overlap with B, so its probability is P(A) minus the overlapping piece P(A∩B). Dividing by P(Bc)=1−P(B) (valid since P(B)=1) gives the conditional probability.
Step-by-Step Solution
- P(A∣Bc)=P(Bc)P(A∩Bc) by definition (needs P(Bc)=0, i.e. P(B)=1, as given).
- A=(A∩B)∪(A∩Bc), a disjoint union, so P(A)=P(A∩B)+P(A∩Bc)⇒P(A∩Bc)=P(A)−P(A∩B).
- P(Bc)=1−P(B). …
- AP EAPCET 2024Set eng-2024-05-20-FN1 markMCQQ.Two digits are selected at random from the digits 1 through 9. If their sum is even, then the probability that both are odd is (A) 83 (B) 21 (C) 85 (D) 43
›Reveal solutionSolution
Conditioning on 'sum even' restricts to same-parity pairs; among those, the odd-odd pairs make up 5/8.
Concept and Intuition
Two digits sum to an even number exactly when they have the same parity (both odd or both even) — an odd plus an even is always odd. This turns the conditional-probability question into a simple counting problem over same-parity pairs only.
Step-by-Step Solution
- Digits 1 through 9: odd ={1,3,5,7,9} (5 digits), even ={2,4,6,8} (4 digits).
- Sum is even ⟺ both digits are odd, or both are even.
- Number of ways to choose 2 odd digits: (25)=10.
- Number of ways to choose 2 even digits: (24)=6.
- Total ways with even sum: 10+6=16. …
- AP EAPCET 2024Set eng-2024-05-20-FN1 markMCQQ.P(A∣A∩B)+P(B∣A∩B)= (A) 1 (B) P(A∪B) (C) P(A∩B) (D) 2
›Reveal solutionSolution
Both conditional probabilities equal 1 because A∩B is a subset of both A and B, so their sum is 2.
Concept and Intuition
Conditioning an event on its own subset (or superset relationship) often collapses to a probability of exactly 1: if E⊆F, then P(F∣E)=1, since knowing E occurred guarantees F occurred too.
Step-by-Step Solution
- P(A∣A∩B)=P(A∩B)P(A∩(A∩B)).
- Since A∩(A∩B)=A∩B (intersecting with A again changes nothing, as A∩B⊆A), this is P(A∩B)P(A∩B)=1.
- Similarly, P(B∣A∩B)=P(A∩B)P(B∩(A∩B))=P(A∩B)P(A∩B)=1.
- Sum =1+1=2. …
- AP EAPCET 2022Set eng-2022-07-06-FN1 markMCQQ.If E and F are events such that P(Fˉ)=0.7 and P(E∩F)=0.2, then P(E∣F) is (A) 2/3 (B) 1/3 (C) 3/4 (D) 1/4
›Reveal solutionSolution
This tests the basic conditional-probability formula together with the complement rule. P(E∣F)=2/3.
Concept and Intuition
P(E∣F) asks: given that F has already happened, what fraction of that reduced sample space does E∩F occupy? It is always P(F)P(E∩F), so first we need P(F) itself, which is given indirectly through its complement.
Step-by-Step Solution
- P(Fˉ)=0.7⇒P(F)=1−0.7=0.3.
- P(E∩F)=0.2 is given directly. …
- AP EAPCET 2021Set eng-2021-08-23-FN1 markMCQQ.Let A and B be two events with P(A)=71, P(A/B)=52 and P(B)=72. Then the value P(B/A) is (A) 51 (B) 495 (C) 54 (D) 53
›Reveal solutionSolution
Chain the conditional-probability definition twice: first get P(A∩B) from P(A/B), then get P(B/A) from that.
Concept and Intuition
Conditional probability is defined as P(E/F)=P(F)P(E∩F). Given one conditional probability, we can back out the joint probability P(A∩B), and then use it (with the definition again, but conditioning the other way) to find the other conditional probability.
Step-by-Step Solution
- P(A/B)=P(B)P(A∩B)⇒P(A∩B)=P(A/B)⋅P(B)=52×72=354.
- Now use P(B/A)=P(A)P(A∩B)=1/74/35. …
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