Q.A die is thrown twice and the sum of the numbers appearing is observed to be 6. What is the conditional probability that the number 4 has appeared at least once?
🔒You're viewing a preview — the full solution, concept, methods & PYQ mapping are locked.
🔒 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 outcomes where the sum is 6, then count favourable cases where 4 appears at least once.
Step 1: Total outcomes when a die is thrown twice: 6×6=36.
Step 2: Outcomes where sum is 6:
(1,5),(2,4),(3,3),(4,2),(5,1) — that’s 5 equally likely outcomes.
Step 3: Among these, outcomes where 4 appears at least once:
(2,4) and (4,2) — that’s 2 outcomes. …
Given that the sum is 6, we restrict to the 5 equally likely outcomes: (1,5), (2,4), (3,3), (4,2), (5,1). Among these, the outcomes containing a 4 are (2,4) and (4,2). So the conditional probability is 52.
Why conditional probability works here
When we say “a die is thrown twice and the sum is 6,” we are no longer in the full sample space of 36 outcomes. The condition shrinks the space to only those pairs that add to 6. Conditional probability is simply: count the favourable outcomes within this restricted space, then divide by the total number of outcomes in the restricted space.
The formula is:
P(A∣B)=P(B)P(A∩B)=number of outcomes in Bnumber of outcomes in both A and B
where B is “sum = 6” and A is “at least one 4 appears.”
Step-by-step reasoning
- List all outcomes where the sum is 6. Since each die shows 1 to 6, the ordered pairs (x,y) with x+y=6 are:
(1,5), (2,4), (3,3), (4,2), (5,1)
That’s 5 equally likely outcomes.
Do not forget that (3,3) is a single ordered pair — it is not counted twice. Also, (2,4) and (4,2) are distinct because the dice are distinct (first throw and second throw).
-
Identify which of these contain at least one 4.
Scan the list:
- (1,5) — no 4
- (2,4) — contains a 4
- (3,3) — no 4
- (4,2) — contains a 4
- (5,1) — no 4
So exactly 2 outcomes satisfy “at least one 4”: (2,4) and (4,2). …
Method: Reduced-sample-space counting for two-dice problems
Use this whenever a die is thrown twice (or two dice are thrown) and a condition on the pair — such as a fixed sum — restricts the outcomes.
Steps
Step 1: List the ordered pairs satisfying the condition.
Treat the two throws as an ordered pair (x,y) so (2,4) and (4,2) are different. Enumerate every pair meeting the condition (for "sum =6": (1,5),(2,4),(3,3),(4,2),(5,1)). This is the reduced space.
Step 2: Count the favourable pairs inside that list. …
Common Mistakes
Mistake 1: Counting (3,3) twice or treating (2,4) and (4,2) as one.
Why it's wrong: the two throws are ordered, so (2,4) and (4,2) are distinct, while (3,3) is a single outcome. Correct approach: list ordered pairs carefully — the sum-6 space has exactly five outcomes.
Mistake 2: Dividing by 36 instead of the restricted count 5. …
Showing the 12 most recent of 45 on this concept.
- 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). …
- 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.
-
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.
-
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).
-
Identify the event of interest: sum = 3. …
-
- 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.
-
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.
-
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-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.
-
Odd numbers from 1 to 9: 1, 3, 5, 7, 9 → 5 odds.
Number of odd–odd pairs: (25)=10.
-
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
-
- 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
-
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.
-
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. …
-
- 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 2026Set 2026-A1 markMCQQ.Vishnu has two jars of marbles, Jar A and Jar B. Jar A contains 3 yellow marbles and 2 green marbles. Jar B contains 4 yellow marbles and 3 green marbles. Vishnu flips a fair coin. If it lands heads, he picks two marbles at random without replacement from Jar A. If it lands tails, he picks two marbles at random with replacement from Jar B. Given that Vishnu picked one yellow and one green marble, what is the probability that they came from Jar B? (A) 4121 (B) 8949 (C) 8940 (D) 4120
›Reveal solutionSolution
P(E∣A)=53 (without replacement), P(E∣B)=4924 (with replacement); Bayes gives P(B∣E)=8940 — option (C).
Likelihoods of drawing one yellow and one green (E).
Jar A (3 yellow, 2 green; two draws without replacement):
P(E∣A)=(25)(13)(12)=106=53.
Jar B (4 yellow, 3 green; two draws with replacement):
P(E∣B)=2⋅74⋅73=4924.
Bayes' theorem with P(A)=P(B)=21 (the 21 cancels): …
- 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
-
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)
-
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.
-
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. …
-
- COMEDK 2026Set 2026-M1 markMCQQ.Samhita faces a three-headed dragon. She wins a "Tactical medal" if she manages to defeat exactly one of the three heads. The battle proceeds head-by-head under the following conditions: The probability of defeating the first head is 31. After a win: if she defeats a head, the probability of defeating the next head is 32. After a loss: if she fails to defeat a head, the probability of defeating the next head is 41. What is the probability that Samhita earns the "Tactical medal"? (A) 7223 (B) 365 (C) 7217 (D) 7219
›Reveal solutionSolution
Summing the three disjoint "exactly one win" paths gives 121+181+81=7219 — option (D).
Set up the conditional probabilities. Let Wi mean "defeats head i" and Li mean "fails":
- P(W1)=31, so P(L1)=32.
- After a win: next-head win probability =32, so next-head loss probability =31.
- After a loss: next-head win probability =41, so next-head loss probability =43.
Earning the medal means exactly one of the three heads is defeated. The three disjoint sequences are W1L2L3, L1W2L3, and L1L2W3.
Path 1 — W1L2L3 (win, then loss after a win, then loss after a loss):
P=31⋅31⋅43=363=121
Path 2 — L1W2L3 (loss, then win after a loss, then loss after a win): …
- COMEDK 2024Set 2024-E1 markMCQQ.A coin is tossed until a head appears or until the coin has been tossed three times. Given that 'head' does not appear on the first toss, what is the probability that the coin is tossed thrice? (A) 21 (B) 83 (C) 81 (D) 41
›Reveal solutionSolution
Given the first toss is a tail, the coin is tossed a third time only if the second toss is also a tail — probability 21.
The coin stops the moment a head appears, or after three tosses. We are told the first toss is a tail (no head on toss 1).
Now the second toss decides:
- Head on toss 2 ⇒ stop after 2 tosses.
- Tail on toss 2 ⇒ a third toss is made. …
- 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. …
🎓Unlock everything free for 14 days
- ✓Full step-by-step solutions
- ✓Concept-first explanations
- ✓Methods, shortcuts & mistakes
- ✓PYQ mapping + timed mock tests
Full access for 14 days. No credit card required.