Q.Ten cards numbered 1 to 10 are placed in a box, mixed up thoroughly and then one card is drawn randomly. If it is known that the number on the drawn card is more than 3, what is the probability that it is an even number?
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).
- If P(A∣B)=P(A), then knowing B tells you nothing about A — the events are independent. That is a special case, not the general rule.
Conditional probability is the foundation of the multiplication theorem, independence, and Bayes' theorem — every "given that" question in this chapter rests on it.
Conditional Probability opens the CBSE Class 12 Probability chapter and is foundational for everything that follows in that unit, including Bayes' theorem and the multiplication rule — making "conditional probability formula class 12 with examples" one of the most searched topics in Class 12 Mathematics. It is equally important for JEE Main and CUET, where conditional probability questions are set almost every year.
Concept: Conditional Probability — we restrict the sample space to the condition given.
Step 1: Total cards: 1 to 10. Condition: number > 3. So the reduced sample space is {4,5,6,7,8,9,10} — 7 equally likely outcomes.
Step 2: Among these, the even numbers are {4,6,8,10} — 4 favourable outcomes.
Step 3: Required probability = total outcomes in conditionfavourable outcomes in condition=74.
The probability is 74.
Given that the drawn card is more than 3, we restrict the sample space to numbers {4,5,6,7,8,9,10}. Among these, the even numbers are {4,6,8,10}. So the required probability is 74.
The key here is conditional probability — we are not finding the probability of drawing an even card from all ten cards. Instead, we already know that the card shows a number greater than 3. That extra information shrinks the set of possible outcomes. The question becomes: Out of the cards that are >3, what fraction are even?
Let’s walk through it step by step.
-
Original sample space
The cards are numbered 1 through 10. So the total number of equally likely outcomes when drawing one card is 10.
-
The condition: number > 3
The cards that satisfy “more than 3” are:
{4,5,6,7,8,9,10}
That’s 7 cards. This becomes our reduced sample space — we only consider these 7 outcomes.
- Favourable outcomes: even numbers among these From the set above, the even numbers are:
{4,6,8,10}
That’s 4 cards.
- Apply the conditional probability formula If A is the event “card is even” and B is the event “card > 3”, then
P(A∣B)=P(B)P(A∩B)
Here A∩B = “even and >3” = {4,6,8,10}, so P(A∩B)=104.
And P(B)=107.
Therefore
P(A∣B)=7/104/10=74.
When the condition reduces the sample space to equally likely outcomes, you can skip the formula and just count:
total outcomes in the reduced spacefavourable outcomes in the reduced space=74.
A common mistake is to forget to restrict the denominator. Some students compute 104 (the probability of an even card overall) — but that ignores the given condition. Always ask: “What is the new set of possible outcomes?”
The required probability is 74.
Method: Reduced-sample-space counting under a numeric condition
Use this when a condition restricts an equally likely draw to a sub-range (e.g. "the number is more than 3") and you want the chance of a further property within that range.
Steps
Step 1: Restrict the sample space to what the condition allows.
From the full list of equally likely outcomes, keep only those satisfying the "given" condition. This restricted list becomes the denominator count.
Step 2: Count how many of the surviving outcomes are favourable.
Within the restricted list, count the outcomes that also satisfy the event you want.
Step 3: Divide directly.
P(A∣B)=#B#(A and B).
Equivalently P(A∩B)/P(B) with a common denominator that cancels. The key discipline is never to divide by the original total — always by the size of the restricted space.
Common Mistakes
Mistake 1: Dividing by the original total of 10 instead of the restricted count.
Why it's wrong: once we know the number is >3, only 7 cards {4,…,10} remain possible, so the denominator is 7, not 10. Correct approach: use the reduced sample space, giving 74, not 104.
Mistake 2: Miscounting the evens in the restricted range.
Why it's wrong: the evens greater than 3 are {4,6,8,10} — four of them; forgetting 10 or including 2 changes the numerator. Correct approach: list the restricted set explicitly before counting favourable outcomes.
Showing the 12 most recent of 45 on this concept.
- 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.
P(E∣R)=P(R∣E)P(E)+P(R∣Ec)P(Ec)P(R∣E)P(E)=32⋅73+31⋅7432⋅73=216+214216=106=53.
✓Final answerThe probability that the number is actually even is 53 — option (D).
- 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
P(both odd∣sum even)=Number of even-sum pairsNumber of odd–odd pairs=1610=85.
TipA common mistake is to treat this as an unconditional probability and compute 3610, which gives 185 — not even among the options. The condition "given sum is even" changes the denominator from 36 to 16.
Watch outAnother pitfall: forgetting that selection is without replacement. If replacement were allowed, the counts would differ, but here the problem implies distinct integers.
✓Final answerThe correct option is (B).
ANSWER: B
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- 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.
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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).
-
Identify the event of interest: sum = 3.
From the list above, there are exactly 2 outcomes: (1,2) and (2,1).
-
Apply conditional probability.
The probability that the sum is 3, given that the sum is less than 6, is:
P(sum=3∣sum<6)=Number of outcomes with sum<6Number of outcomes with sum=3 and sum<6
Since every outcome with sum = 3 automatically satisfies sum < 6, the numerator is just 2. The denominator is 10.
So:
P=102=51
TipYou can also think of this as: "Out of the 10 equally likely ways to get a sum less than 6, exactly 2 give a sum of 3." That’s the same as 102.
✓Final answerThe correct option is (C) 51.
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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).
Those in which 5 appears at least once: (3,5) and (5,3) — 2 outcomes.
P(5 appears∣sum=8)=52.
✓Final answerThe correct option is (B) — 52
- 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.
-
Identify which of these have the other side black.
Only the red side R3 (from card C) has a black other side. The other two red sides (R1,R2) have red on the other side.
-
Compute the conditional probability.
P(other side black∣top side red)=total number of red sidesnumber of favorable red sides=31.
Watch outThe common mistake is to forget that the all-red card contributes two red sides to the sample space, making it twice as likely as the mixed card once we condition on seeing red.
TipA neat way to think: "Probability = (number of red sides with black opposite) / (total number of red sides)." This avoids the card-counting trap entirely.
✓Final answerThe correct option is (D).
ANSWER: D
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- 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.
Among the sum-12 pairs, the only equal pair is (6,6).
So there is exactly 1 favorable outcome.
-
Apply conditional probability
P(equal∣sum=12)=total pairs with sum 12number of equal pairs with sum 12=51.
Watch outA common mistake is to compute 641 (since only one equal pair overall sums to 12 out of all 64 pairs). But the condition “given sum = 12” changes the denominator to 5, not 64.
TipAlways re-read: “given that the sum is 12” means we only care about the 5 outcomes listed. Conditional probability shrinks the universe.
✓Final answerThe correct option is (B).
ANSWER: B
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- 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
Sanity check (symmetry): By the symmetry (a,b)↦(7−a,7−b), P(sum>7)=P(sum<7). Since P(sum=7)=366=61, each of the other two must be 21(1−61)=125 — which confirms the count.
✓Final answerThe correct option is (C) — 125.
ANSWER: C
- 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.
Only (4,5,6) sums to 15.
-
Count favorable ordered triples.
The triple (4,5,6) can appear in 3!=6 orders. So there are 6 ordered triples that satisfy both conditions.
-
Compute the conditional probability.
P(sum=15∣distinct AP)=total ordered triplesfavorable ordered triples=366=61.
TipA common mistake is to treat the unordered triples as equally likely — they are not, because each unordered triple corresponds to 6 ordered outcomes. Always count ordered rolls when dice are distinct.
Watch outDo not forget that the condition “three different numbers” already excludes permutations with repeats; but here all AP triples are automatically distinct, so no extra filtering is needed.
✓Final answerThe correct option is (B).
ANSWER: B
- COMEDK 2021Set 2021-B1 markMCQQ.At a certain university 4% of male students are over 6 feet tall and 1% of female students are over 6 feet tall. The total student population is divided in the ratio 3 : 2, in favor of female students. If a student is selected at random from amongst all those over 6 feet tall, what is the probability that the student is a female? (A) 1/3 (B) 2/5 (C) 3/11 (D) 3/5
›Reveal solutionSolution
Bayes' theorem gives P(female∣>6ft)=0.0220.006=113.
Population split 3:2 in favour of females ⇒ P(F)=53=0.6, P(M)=52=0.4.
Tall fractions: P(T∣F)=0.01, P(T∣M)=0.04.
By Bayes' theorem:
P(F∣T)=P(T∣F)P(F)+P(T∣M)P(M)P(T∣F)P(F)=0.01×0.6+0.04×0.40.01×0.6.
=0.006+0.0160.006=0.0220.006=226=113.
✓Final answerThe correct option is (C) — 3/11
- 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).
P(A)=54−53+103=51+103=102+103=105=21.
Consistency check. With P(A)=21, P(B)=53, P(A∩B)=103: note P(A)P(B)=21⋅53=103=P(A∩B), so A and B are independent — entirely consistent with P(A/B)=21=P(A). And P(A∪B)=21+53−103=105+6−3=108=54. ✓
✓Final answerThe correct option is (B) — 21.
ANSWER: B
- 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.
So a third toss happens exactly when the second toss is a tail:
P(tossed thrice∣first is tail)=P(tail on toss 2)=21
✓Final answerThe probability is 21 — option (A).
- 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).
P(2nd red∣red first)=74
Total probability:
P(2nd red)=72⋅76+75⋅74=4912+4920=4932
✓Final answerP(second ball red)=4932 — option (B).
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