Q.If P(B)=53, P(A∣B)=21 and P(A∪B)=54, then P((A∪B)′)+P(A′∪B) equals
(A) 51
(B) 54
(C) 21
(D) 1
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🔒 Start your 14-day free trial to unlock the full solution →Concept understanding — Probability Complement Rule
The Probability Complement Rule
Every event A splits the sample space in two: outcomes where A happens, and outcomes where it does not. The second group is the complement of A, written A′ (also Ac or Aˉ). Because exactly one of the two must occur, their probabilities together fill the whole space:
P(A)+P(A′)=1⟹P(A′)=1−P(A).
That is the complement rule: the probability that A does not happen is 1 minus the probability that it does.
Why It Holds
A and A′ are mutually exclusive (no outcome lies in both) and exhaustive (together they are the entire sample space S, with P(S)=1). So P(A)+P(A′)=P(S)=1, and rearranging gives the rule.
A Simple Example
For a fair die, P(six)=61, so P(not six)=1−61=65.
Why It Is So Useful: the "At Least One" Trick
Counting "at least one" directly often means adding many separate cases, while its complement, "none," is a single easy case. For instance, the probability of at least one head in three tosses of a fair coin:
P(at least one head)=1−P(no heads)=1−(21)3=1−81=87.
Computing "no heads" once is far quicker than summing the one-head, two-head and three-head cases separately. …
Given P(B)=53, P(A∣B)=21, P(A∪B)=54.
P(A∩B)=P(A∣B)P(B)=21⋅53=103, and P(A)=54−53+103=21.
P((A∪B)′)=1−P(A∪B)=1−54=51. …
P((A∪B)′)=51 and P(A′∪B)=54, so their sum is 1 — option (D).
Setup
We are given P(B)=53, P(A∣B)=21, P(A∪B)=54. First recover P(A∩B) and P(A):
P(A∩B)=P(A∣B)P(B)=21⋅53=103,
P(A)=P(A∪B)−P(B)+P(A∩B)=54−53+103=21.
First term
By the complement rule, P((A∪B)′)=1−P(A∪B)=1−54=51.
Second term
Use De Morgan's law: (A′∪B)′=A∩B′, so P(A′∪B)=1−P(A∩B′).
Since A splits into the parts inside and outside B, P(A∩B′)=P(A)−P(A∩B)=21−103=51. …
Method: Complement rule and De Morgan for compound expressions
Use this for expressions built from unions, complements and conditionals that must each be simplified before adding.
Steps
Step 1: Simplify each complemented compound with De Morgan / complement rule.
P((A∪B)′)=1−P(A∪B),(A′∪B)′=A∩B′.
So P(A′∪B)=1−P(A∩B′).
Step 2: Reduce the leftover joint terms to known quantities. …
Common Mistakes
Mistake 1: Writing P(A′∪B)=1−P(A∪B).
Why it's wrong: the complement of A∪B is A′∩B′, not A′∪B. Correct approach: use De Morgan — (A′∪B)′=A∩B′, so P(A′∪B)=1−P(A∩B′).
Mistake 2: Leaving P(A∩B′) unreduced. …
- CBSE 2026Set 65/2/11 markMCQQ.For two events A and B such that P(A)=0 and P(B)=1, P(A′/B′)= (A) 1−P(A/B) (B) 1−P(A′/B) (C) P(B′)1−P(A∩B) (D) P(B′)1−P(A∪B)
›Reveal solutionSolution
We need to find P(A′∣B′). By applying the definition of conditional probability, De Morgan's Law, and the complement rule, we can express this as P(B′)1−P(A∪B), which corresponds to option (D).
Let's break down this problem by first understanding the core concepts involved: conditional probability and the complement rule.
Conditional probability, P(X∣Y), represents the probability of event X occurring given that event Y has already occurred. Its definition is fundamental:
P(X∣Y)=P(Y)P(X∩Y), provided P(Y)=0.
The complement rule states that the probability of an event not happening is 1 minus the probability of it happening. If X′ denotes the complement of event X (i.e., X does not occur), then:
P(X′)=1−P(X).
We are asked to find P(A′∣B′), which means "the probability that event A does not occur, given that event B does not occur."
Now, let's work through the problem step-by-step.
- Apply the definition of conditional probability. Using the formula P(X∣Y)=P(Y)P(X∩Y), we replace X with A′ and Y with B′.
P(A′∣B′)=P(B′)P(A′∩B′)
The problem states $P(B) \ne 1$. This is important because it implies $P(B') = 1 - P(B) \ne 0$, ensuring that the denominator is not zero and the conditional probability is well-defined.2. Simplify the numerator using De Morgan's Law.
The term A′∩B′ represents the event where neither A nor B occurs. This is equivalent to the event that A∪B (either A or B or both occur) does not occur. This is a direct application of De Morgan's Law for sets:
(A∪B)′=A′∩B′
Therefore, we can rewrite the numerator:P(A′∩B′)=P((A∪B)′)
- Apply the complement rule to the numerator. Now we have P((A∪B)′). Using the complement rule P(X′)=1−P(X), where X is the event (A∪B):
P((A∪B)′)=1−P(A∪B)
- Substitute back into the conditional probability formula. Substitute the simplified numerator back into the expression from Step 1: …
- CBSE 2025Set 65/2/11 markMCQQ.If E and F are two events such that P(E)>0 and P(F)=1, then P(E′∣F′) is: (A) P(F′)P(E′) (B) 1−P(E′∣F) (C) 1−P(E∣F) (D) P(F′)1−P(E∪F)
›Reveal solutionSolution
Use the complement rule and conditional probability definition: P(E′∣F′)=P(F′)P(E′∩F′), then recognize that E′∩F′=(E∪F)′ to arrive at option (D): P(F′)1−P(E∪F).
The heart of this problem is understanding what conditional probability means when both events are complemented, and how set operations interact with complements.
Conditional probability P(A∣B) asks: "Given that B has occurred, what is the probability of A?" The formula is always
P(A∣B)=P(B)P(A∩B).
When we want P(E′∣F′), we're asking: "Given that F did not occur, what is the probability that E also did not occur?" So we need the intersection E′∩F′ in the numerator.
The key insight is recognizing what E′∩F′ represents. By De Morgan's law, the region where neither E nor F occurs is precisely the complement of their union:
E′∩F′=(E∪F)′.
This transforms our problem into something we can express in terms of P(E∪F).
Step-by-step derivation:
- Write the definition of conditional probability for P(E′∣F′):
P(E′∣F′)=P(F′)P(E′∩F′).
- Apply De Morgan's law to the numerator: The event "not E and not F" is the same as "not (E or F)":
E′∩F′=(E∪F)′.
- Express the complement in terms of probability:
P(E′∩F′)=P((E∪F)′)=1−P(E∪F).
- Substitute back into the conditional probability formula:
P(E′∣F′)=P(F′)1−P(E∪F).
This matches option (D) exactly.
--- …
- CBSE 2026Set A1 markMCQQ.1−P(A′∩B′)=(a) P(A∩B)(b) P(A∪B)(c) P(A)(d) P(B)
›Reveal solutionSolution
1−P(A′∩B′)=P(A∪B).
By De Morgan's law,
A′∩B′=(A∪B)′.
So …
- CBSE 2025Set ANNUAL1 markMCQQ.A problem is given to three students whose chances of solving it are 1/4, 1/5 and 1/6 respectively. Then, the probability that the problem is solved is –(i) 1/120(ii) 1/4(iii) 1/2(iv) 3/4
›Reveal solutionSolution
It's easier to find the probability that NONE of the three solve it, then subtract from 1.
Chances of solving: 1/4, 1/5, 1/6, so chances of NOT solving: 3/4, 4/5, 5/6 respectively (independent students).
P(none solves)=43×54×65=12060=21.
…
- CBSE 2024Set EX1 markQ.The probability of A winning the race is 31 and that of B is 41. In this race, find the probability that neither A nor B can win the race.
›Reveal solutionSolution
In one race only one person can win, so the events "A wins" and "B wins" are mutually exclusive. P(A or B)=31+41=127; neither =1−127=125.
Concept. For mutually exclusive events, P(A∪B)=P(A)+P(B). "Neither wins" is the complement of "A or B wins".
Add the winning chances. …
- CBSE 2023Set M1 markQ.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).
›Reveal solutionSolution
Tests De Morgan's law with the addition rule; P(A′∩B′)=83.
By De Morgan's law, P(not A and not B)=P(A′∩B′)=P((A∪B)′)=1−P(A∪B).
Using the addition rule: …
- CBSE 2021Set I1 markMCQQ.P(A)+P(A′)=(a) 0(b) 1(c) −1(d) P(S)
›Reveal solutionSolution
Complementary probabilities sum to 1.
An event A and its complement A′ together cover the whole sample space S and are mutually exclusive.
…
- CBSE 2021Set I1 markMCQQ.1−P(A′∩B′)=(a) P(A∩B)(b) P(A∪B)(c) P(A)(d) P(B)
›Reveal solutionSolution
A′∩B′ is the complement of A∪B; 1 minus its probability gives P(A∪B).
By De Morgan's law, A′∩B′=(A∪B)′.
Using the complement rule P(E′)=1−P(E):
…
- CBSE 2020Set 65/3/11 markQ.An unbiased coin is tossed 4 times. Find the probability of getting at least one head.
›Reveal solutionSolution
The complement approach is cleanest: find the probability of no heads (all tails), then subtract from 1. The probability of at least one head is 1615.
Why the complement works
When a problem asks for "at least one" of something, you face the tedious task of adding up many cases: exactly one head, exactly two heads, exactly three heads, or all four heads. The complement sidesteps this entirely. There's only one way to fail the "at least one head" condition: get zero heads, meaning all four tosses land tails. Calculate that single probability, subtract from 1, and you're done.
Solution
-
Identify the complement event
"At least one head" means one or more heads. The opposite is "no heads at all," which is the same as getting tails on every single toss.
-
Find the probability of all tails
Each toss is independent, and for an unbiased coin P(Tail)=21. The probability of tails on all four tosses is: …
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- CBSE 2019Set ANNUAL1 markMCQQ.P(A)+P(A′)=?(a) 0(b) 1(c) −1(d) P(E)
›Reveal solutionSolution
P(A)+P(A′)=1.
The complement A′ consists of all outcomes not in A, so A and A′ are mutually exclusive and exhau …
- CBSE 2018Set ANNUAL1 markQ.Match the Column-A item 'A pair of coins are thrown simultaneously. What is the total chance of getting at least one head?' with the correct entry from Column-B. Column-B options (as printed, unordered):(1) 1;(2) 6;(3) 3;(4) 5;(5) 4.
›Reveal solutionSolution
List all equally-likely outcomes of two coin tosses; 'at least one head' excludes only the all-tails case.
Sample space for two coins tossed together: {HH,HT,TH,TT} — 4 equally likely outcomes.
'At least one head' is satisfied by HH,HT,TH — that's 3 favourable outcomes.
…
- CBSE 2018Set ANNUAL1 markMCQQ.Three coins are tossed. The probability of at least one head is(a) 81(b) 83(c) 86(d) 87
›Reveal solutionSolution
Use the complement: at least one head is the opposite of no heads at all.
P(no head in 3 tosses)=(21)3=81 …
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