Q.Two dice are thrown. If it is known that the sum of numbers on the dice was less than 6, the probability of getting a sum 3 is
(A) 181
(B) 185
(C) 51
(D) 52
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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 restrict the sample space to the given condition and count favourable outcomes within it.
Step 1: Identify the reduced sample space.
The condition is that the sum is less than 6. Possible sums are 2, 3, 4, 5. List all ordered pairs (a,b) with 1≤a,b≤6 that satisfy this:
- Sum 2: (1,1) → 1 outcome
- Sum 3: (1,2), (2,1) → 2 outcomes
- Sum 4: (1,3), (2,2), (3,1) → 3 outcomes
- Sum 5: (1,4), (2,3), (3,2), (4,1) → 4 outcomes
Total outcomes under condition = 1+2+3+4=10.
Step 2: Count favourable outcomes.
Favourable event: sum exactly 3. From above, that gives 2 outcomes. …
We use conditional probability: restrict the sample space to outcomes where the sum is less than 6 (10 equally likely pairs), then count how many of those give a sum of 3 (2 pairs). The probability is 102=51.
The key here is conditional probability — we are not finding the probability of sum 3 in the full sample space of 36 outcomes. Instead, we are given extra information: the sum is less than 6. This reduces the set of possible outcomes, and we must find the probability within that restricted set.
Think of it this way: when you know the sum is less than 6, you are no longer considering all 36 pairs. You only care about the ones that satisfy that condition. The probability becomes:
P(sum=3∣sum<6)=Number of outcomes with sum<6Number of outcomes with sum=3 and sum<6
Since sum 3 is automatically less than 6, the numerator is just the number of ways to get sum 3.
Let’s work it out step by step.
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Full sample space: When two dice are thrown, each die shows 1 to 6. Total outcomes = 6×6=36. All pairs are equally likely.
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Restricted condition — sum less than 6: List all pairs (a,b) where a+b≤5 (since sum is an integer, less than 6 means 2, 3, 4, or 5).
- Sum = 2: (1,1) → 1 outcome
- Sum = 3: (1,2), (2,1) → 2 outcomes
- Sum = 4: (1,3), (2,2), (3,1) → 3 outcomes
- Sum = 5: (1,4), (2,3), (3,2), (4,1) → 4 outcomes Total outcomes with sum < 6 = 1+2+3+4=10.
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Favorable outcomes — sum exactly 3: From the list above, there are 2 outcomes: (1,2) and (2,1). …
Method: Conditional probability with a restricted sample space
Use this when a condition ("given the sum is less than 6", "given the number is even") is imposed and you must find the probability of a further event within that restricted set.
Steps
Step 1: Build the full equally-likely sample space.
For two dice this is all 6×6=36 ordered pairs.
Step 2: Reduce to the outcomes satisfying the condition B.
Keep only the outcomes obeying the given condition and count them — this count becomes the denominator, replacing the full 36.
Step 3: Count outcomes satisfying both the condition and the target event A. …
Common Mistakes
Mistake 1: Using the full 36 outcomes as the denominator, 362=181.
Why it's wrong: the condition "sum <6" has already eliminated most pairs, so 36 is not the conditioned total (this yields the distractor 181). Correct approach: the denominator is the number of outcomes with sum <6, which is 10, giving 102=51. …
Showing the 12 most recent of 45 on this concept.
- KCET 2021Set A-11 markMCQQ.Two dice are thrown. If it is known that the sum of numbers on the dice was less than 6 the probability of getting a sum as 3 is (A) 181 (B) 185 (C) 51 (D) 52
›Reveal solutionSolution
We use conditional probability: reduce the sample space to only those outcomes where the sum is less than 6, then find the fraction of those that give a sum of exactly 3. The answer is 51.
The key idea here is conditional probability — the probability of one event given that another event has already occurred. When we say "if it is known that the sum was less than 6", we are no longer considering all 36 possible outcomes of throwing two dice. Instead, we restrict ourselves to only those outcomes that satisfy the condition, and then ask: within this smaller set, what fraction gives a sum of 3?
Let’s work it out step by step.
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List all possible outcomes when two dice are thrown.
Each die shows a number from 1 to 6. The total number of ordered pairs (a,b) is 6×6=36.
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Identify the condition: sum less than 6.
The possible sums are 2, 3, 4, and 5 (since sum = 1 is impossible with two dice). Let’s list all ordered pairs that give each sum:
- Sum = 2: (1,1) → 1 outcome
- Sum = 3: (1,2),(2,1) → 2 outcomes
- Sum = 4: (1,3),(2,2),(3,1) → 3 outcomes
- Sum = 5: (1,4),(2,3),(3,2),(4,1) → 4 outcomes
Total outcomes with sum < 6: 1+2+3+4=10.
Watch outA common mistake is to forget that (1,2) and (2,1) are different outcomes. Dice are distinct, so order matters. Always count ordered pairs unless the problem explicitly says "identical dice" (which is rare in such problems).
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Identify the event of interest: sum = 3. …
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- 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). …
- COMEDK 2025Set 2025-M1 markMCQQ.Three fair dice are thrown. What is the probability of getting a total of 15 given that they exhibit three different numbers that are in arithmetic progression? (A) 81 (B) 61 (C) 41 (D) 21
›Reveal solutionSolution
The problem asks for the conditional probability that three dice sum to 15, given that the three numbers shown are distinct and form an arithmetic progression. By listing all such triples and counting those summing to 15, the probability is found to be 1/2.
Concept and intuition
We need P(sum=15∣distinct AP). The condition restricts the outcomes to only those triples (a,b,c) with a<b<c (since dice are fair, order matters but we can treat ordered rolls; however the condition “three different numbers” and “arithmetic progression” is symmetric). The key is to enumerate all possible ordered triples of distinct numbers from {1,2,3,4,5,6} that are in arithmetic progression, then count how many of those sum to 15. Because the dice are fair, each ordered triple is equally likely, so the conditional probability is just the ratio of favorable ordered triples to total ordered triples satisfying the condition.
Step-by-step reasoning
- Characterize arithmetic progressions of three distinct numbers from 1 to 6. Three numbers x,y,z (with x<y<z) are in AP iff 2y=x+z. Since they are distinct and from 1 to 6, the possible triples (unordered) are:
(1,2,3), (1,3,5), (2,3,4), (2,4,6), (3,4,5), (4,5,6).
Check: For (1,2,3): 2⋅2=1+3; (1,3,5): 2⋅3=1+5; etc. That’s all.
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Count ordered triples satisfying the condition.
For each unordered triple, the three numbers are distinct, so they can appear in any order on the three dice. That gives 3!=6 permutations per triple.
Total ordered triples satisfying the condition = 6×6=36.
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Identify which of these triples sum to 15.
Compute sums of the unordered triples:
(1,2,3)(1,3,5)(2,3,4)(2,4,6)(3,4,5)(4,5,6)→6,→9,→9,→12,→12,→15. …
- 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 2019Set A-11 markMCQQ.A man speaks truth 2 out of 3 times. He picks one of the natural numbers in the set S={1,2,3,4,5,6,7} and reports that it is even. The probability that it is actually even is (A) 52 (B) 51 (C) 101 (D) 53
›Reveal solutionSolution
By Bayes' theorem the probability is 53 — option (D).
The set S={1,2,3,4,5,6,7} has 3 even numbers (2,4,6) and 4 odd numbers, and one number is picked at random.
Let E = "the number is even" and R = "the man reports it as even."
Priors.
P(E)=73,P(Ec)=74.
Likelihoods. He tells the truth with probability 32 and lies with probability 31.
- If the number really is even, a truthful report says "even": P(R∣E)=32.
- If the number is odd, only a lie reports "even": P(R∣Ec)=31.
Bayes' theorem. …
- KCET 2018Set A-11 markMCQQ.In a simultaneous throw of a pair of dice, the probability of getting a total more than 7 is (A) 127 (B) 365 (C) 125 (D) 367
›Reveal solutionSolution
Count the ordered outcomes whose sum exceeds 7 out of the 36 equally likely outcomes of a pair of dice.
Step 1 — The sample space.
Each die shows one of 6 faces, and the two dice are independent, so
n(S)=6×6=36
All 36 ordered pairs (a,b) are equally likely, so classical probability applies:
P(E)=n(S)n(E)
Step 2 — Count the favourable outcomes (sum >7, i.e. sum =8,9,10,11,12).
Sum Ordered pairs Count 8 (2,6),(3,5),(4,4),(5,3),(6,2) 5 9 (3,6),(4,5),(5,4),(6,3) 4 10 (4,6),(5,5),(6,4) 3 11 (5,6),(6,5) 2 12 (6,6) 1 n(E)=5+4+3+2+1=15
Step 3 — Probability.
P(sum>7)=3615=125 …
- COMEDK 2025Set 2025-E1 markMCQQ.Two numbers are selected at random from integers 1 to 9 . If their sum is even, what is the probability that both the numbers are odd? (A) 94 (B) 85 (C) 61 (D) 32
›Reveal solutionSolution
This is a conditional probability problem: given that the sum of two numbers from 1–9 is even, we want the probability both are odd. The answer is 5/8, option (B).
We are selecting two numbers from 1 to 9 without replacement (since "selected at random" from distinct integers usually implies no repetition). The sum is even only if both numbers are odd or both are even. So the condition restricts us to those pairs. The question asks: among those pairs with an even sum, what fraction consists of two odd numbers?
1. Count total possible pairs (without replacement)
From 1 to 9, there are 9 numbers. The number of ways to choose any two distinct numbers is
(29)=36.
2. Count pairs with an even sum
A sum is even when both numbers have the same parity.
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Odd numbers from 1 to 9: 1, 3, 5, 7, 9 → 5 odds.
Number of odd–odd pairs: (25)=10.
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Even numbers from 1 to 9: 2, 4, 6, 8 → 4 evens.
Number of even–even pairs: (24)=6.
So total pairs with an even sum:
10+6=16.
3. Apply conditional probability
We want
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- 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). …
- 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. …
- COMEDK 2024Set 2024-M1 markMCQQ.A and B each have a calculator which can generate a single digit random number from the set {1,2,3,4,5,6,7,8}. They can generate a random number on their calculator. Given that the sum of the two numbers is 12 , then the probability that the two numbers are equal is (A) 645 (B) 51 (C) 161 (D) 81
›Reveal solutionSolution
We are asked for the conditional probability that two numbers are equal given their sum is 12.
The only equal pair summing to 12 is (6,6), and there are 5 total pairs summing to 12.
So the probability is 51, which corresponds to option (B).
Concept and intuition
This is a classic conditional probability problem: we are not interested in all possible outcomes, only those where the sum is exactly 12. The phrase “given that the sum is 12” means we restrict our universe to those pairs. Then we count how many of those restricted outcomes have the two numbers equal. The trap is to forget to restrict the denominator — many students mistakenly use the total number of all possible pairs (64) instead of only the favorable-sum pairs.
Step-by-step solution
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Identify the sample space
Each of A and B picks a digit from {1,2,…,8}.
Total possible ordered pairs (a,b): 8×8=64.
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List all pairs with sum 12
We need a+b=12, with 1≤a,b≤8.
Possible values for a:
- If a=4, then b=8
- If a=5, then b=7
- If a=6, then b=6
- If a=7, then b=5
- If a=8, then b=4
So the pairs are:
(4,8), (5,7), (6,6), (7,5), (8,4)
That’s 5 ordered pairs.
- Count the favorable outcomes “The two numbers are equal” means a=b. …
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- COMEDK 2024Set 2024-E1 markMCQQ.Suppose we have three cards identical in form except that both sides of the first card are coloured red, both sides of the second are coloured black, and one side of the third card is coloured red and the other side is coloured black. The three cards are mixed and a card is picked randomly. If the upper side of the chosen card is coloured red, what is the probability that the other side is coloured black. (A) 61 (B) 21 (C) 0 (D) 31
›Reveal solutionSolution
This is a classic conditional probability problem (often called the "three cards" or "Bertrand's box" variant). The key is that seeing a red side updates the probability space to only the red sides, and among those, only one belongs to the mixed card. The answer is 1/3.
We are asked: given that the visible side is red, what is the probability that the other side is black? This is not simply "one of the two remaining cards has a black other side" because the cards are not equally likely once we condition on the observation.
Concept and Intuition
The pitfall is to think: "We see red, so the card is either the all-red or the mixed card. That's two possibilities, so the chance is 1/2." But this ignores that the all-red card has two red sides, while the mixed card has only one red side. When we pick a card at random and then look at a random side, each of the six sides is equally likely to be the one we see. Seeing red eliminates the three black sides, leaving only the three red sides. Among those three red sides, two belong to the all-red card and only one belongs to the mixed card. So the probability that the other side is black is 1/3.
Step-by-step reasoning
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Label the sides.
Let the cards be:
- Card A: both sides red (sides R1,R2)
- Card B: both sides black (sides B1,B2)
- Card C: one red, one black (sides R3,B3)
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Count equally likely outcomes.
When we pick a card uniformly at random and then look at a random side, there are 3×2=6 equally likely side-views. Each of the six sides has probability 1/6 of being the one we see.
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Condition on seeing a red side.
The red sides are: R1,R2 (from card A) and R3 (from card C). That's 3 red sides. So the conditional space has 3 equally likely possibilities. …
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- 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. …
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