Q.Refer to Question 74 above. The probability that exactly two of the three balls were red, the first ball being red, is
(A) 31
(B) 74
(C) 2815
(D) 285
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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). …
This refers to the box of 5 red and 3 black balls (Question 74), with three balls drawn one by one without replacement. Following the official reading, we want the probability of the ordered outcome red, red, black — the first ball red and exactly two of the three red: …
For the box of 5 red and 3 black balls (Q74), the probability of the sequence red, red, black is 85⋅74⋅63=285 — the official answer, option (D).
The setup (from Question 74)
The box has 5 red and 3 black balls (8 in all), and three balls are drawn one by one without replacement. We are told the first ball is red and asked for the probability that exactly two of the three drawn are red.
The computation
The first ball is red and exactly two of the three are red, taken as the ordered outcome red, red, black (R, R, B):
P(R)=85,P(R after R)=74,P(B after R,R)=63.
Multiplying along the branch:
P=85⋅74⋅63=33660=285. …
Method: Sequential draws via the multiplication theorem along a branch
Use this when balls are drawn one by one without replacement and you want the probability of a specific ordered sequence.
Steps
Step 1: Write the chain of conditional probabilities.
For a sequence of outcomes, multiply along the branch, updating counts after each draw:
P=P(1st)⋅P(2nd∣1st)⋅P(3rd∣1st,2nd)⋯
Step 2: Update the pool at every step.
Each draw removes one ball, so both the favourable count and the total drop by one for the next factor. …
Common Mistakes
Mistake 1: Not updating the counts after each draw.
Why it's wrong: without replacement, after drawing a red the pool becomes 4 red of 7, etc.; reusing 5/8 each time is the with-replacement error. Correct approach: multiply 85⋅74⋅63, decrementing both counts.
Mistake 2: Summing every "exactly two red" order when the wording fixes one. …
Showing the 12 most recent of 45 on this concept.
- COMEDK 2021Set 2021-B1 markMCQQ.An urn contains 5 red and 5 black coloured balls. A ball is picked at random, its colour noted and then is put back into the urn. Now, additional two balls of the same colour are put into the urn and then a ball is drawn at random. What is the probability that the ball now chosen is red. (A) 7/24 (B) 1/2 (C) 5/8 (D) 2/3
›Reveal solutionSolution
By symmetry the second-draw red probability averages to 21.
Start: 5 red, 5 black (10 total). First ball is drawn, replaced, then 2 more of the same colour are added, so the urn always has 12 balls before the second draw.
- First ball red (P=105=21): urn now 7R, 5B ⇒ P(red)=127. …
- COMEDK 2024Set 2024-M1 markMCQQ.An urn contains 2 white and 2 black balls. A ball is drawn at random. If it is white it is not replaced into the urn. Otherwise it is replaced along with another ball of the same colour. The process is repeated. The probability that the third ball drawn is black is (A) 3017 (B) 6037 (C) 6031 (D) 3023
›Reveal solutionSolution
Conditioning on the first two draws (white -> not replaced; black -> replaced plus one extra black) and using total probability gives P(3rd black)=3023 — option (D).
Rules. Start with 2 white, 2 black (total 4). Drawing white removes it (whites −1, total −1). Drawing black puts it back and adds one more black (blacks +1, total +1).
First two draws and the composition just before the 3rd draw
- WW: 42⋅31=61; urn becomes W0, B2 (total 2) ⇒P(black)=1.
- WB: 42⋅32=31; urn becomes W1, B3 (total 4) ⇒P(black)=43.
- BW: 42⋅52=51; urn becomes W1, B3 (total 4) ⇒P(black)=43.
- BB: 42⋅53=103; urn becomes W2, B4 (total 6) ⇒P(black)=32. …
- COMEDK 2025Set 2025-E1 markMCQQ.A pot contains 5 red and 2 green balls. A ball is drawn at random from this pot. If a drawn ball is green, then a red ball is added to the pot. If a drawn ball is red, then a green ball is added to the pot, while the original ball drawn is not replaced in the pot. Now a second ball is drawn at random from the pot, what is the probability that the second ball drawn is a red ball? (A) 4912 (B) 4932 (C) 73 (D) 4927
›Reveal solutionSolution
Condition on the first draw: P(2nd red)=72⋅76+75⋅74=4932.
Start: 5 red, 2 green, total 7. The first ball is not replaced, and a ball of the other colour is added.
Case 1 — first ball is green. P=72.
Remove that green (5R,1G), then add a red ⇒6R,1G (total 7).
P(2nd red∣green first)=76
Case 2 — first ball is red. P=75.
Remove that red (4R,2G), then add a green ⇒4R,3G (total 7). …
- 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 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 2023Set 2023-E1 markMCQQ.Bag A contains 3 white and 2 red balls. Bag B contains only 1 white ball. A fair coin is tossed. If head appears then 1 ball is drawn at random from bag A and put into bag B. However if tail appears then 2 balls are drawn at random from bag A and put into bag B. Now one ball is drawn at random from bag B. Given that the drawn ball from B is white, the probability that head appeared on the coin is (A) 3023 (B) 2312 (C) 2311 (D) 3019
›Reveal solutionSolution
Computing P(white drawn∣H)=54 and P(white∣T)=1511, Bayes' theorem gives P(H∣white)=2312.
Head (transfer 1 ball from A(3W,2R) to B(1W), then draw from B's 2 balls):
P(white)=53(1)+52(21)=53+51=54.
Tail (transfer 2 balls from A to B(1W), then draw from B's 3 balls):
P(WW)=103⇒P(white)=1,P(WR)=106⇒32,P(RR)=101⇒31. …
- 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. …
- 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. …
- 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 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): …
- KCET 2020Set A-11 markMCQQ.The probability of solving a problem by three persons A, B and C independently is 21, 41 and 31 respectively. Then the probability of the problem is solved by any two of them is (A) 121 (B) 41 (C) 241 (D) 81
›Reveal solutionSolution
The problem asks for the probability that exactly two of the three persons solve it. We compute the sum of probabilities for each pair solving while the third fails, giving 81.
The key idea: "solved by any two of them" means exactly two solve it, not at least two. The third person must fail. Since A, B, and C work independently, we multiply their individual probabilities for each specific outcome and then add the three possible cases.
A common mistake is to include the case where all three solve it. That would be "at least two", not "any two". The phrase "any two" in probability problems almost always means exactly two.
Let’s denote:
- P(A)=21, so P(A fails)=1−21=21
- P(B)=41, so P(B fails)=1−41=43
- P(C)=31, so P(C fails)=1−31=32
We want exactly two successes. There are three mutually exclusive ways this happens:
-
A and B solve, C fails
Probability = P(A)×P(B)×P(C fails)
=21×41×32=242=121
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A and C solve, B fails
Probability = P(A)×P(C)×P(B fails)
=21×31×43=243=81
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B and C solve, A fails
Probability = P(B)×P(C)×P(A fails) …
- 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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