Q.If a leap year is selected at random, what is the chance that it will contain 53 tuesdays?
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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 need the probability of 53 Tuesdays given the year is a leap year.
A leap year has 366 days, which is 52 weeks (364 days) plus 2 extra days. These 2 extra days can be any of the 7 consecutive pairs starting from Sunday: (Sun, Mon), (Mon, Tue), (Tue, Wed), (Wed, Thu), (Thu, Fri), (Fri, Sat), (Sat, Sun). …
The key idea is that a leap year has 366 days = 52 weeks + 2 extra days. The chance of 53 Tuesdays equals the probability that one of those two extra days is a Tuesday. Since the two extra days are equally likely to be any consecutive pair of weekdays, the required probability is 72.
Why conditional probability?
This problem is a classic application of equally likely outcomes — not conditional probability in the strict sense, but the reasoning is similar: we are counting favourable arrangements among all possible arrangements of the extra days. A leap year has 366 days, which is exactly 52 weeks (giving 52 Tuesdays) plus 2 extra days. For the year to have 53 Tuesdays, at least one of those two extra days must be a Tuesday.
Step-by-step reasoning
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Structure of a leap year
A leap year has 366 days.
366=52×7+2
So there are 52 complete weeks (each containing one Tuesday) and 2 additional days.
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What are the possible extra days?
The two extra days are consecutive. If the year starts on a particular weekday, the extra days are the first two days of the year. But since the year is selected at random, the starting day is equally likely to be any of the 7 weekdays.
Therefore, the pair of extra days can be any of the 7 possible consecutive pairs:
(Monday, Tuesday), (Tuesday, Wednesday), (Wednesday, Thursday), (Thursday, Friday), (Friday, Saturday), (Saturday, Sunday), (Sunday, Monday).
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Counting favourable outcomes
We need the year to have 53 Tuesdays. That happens if either of the two extra days is a Tuesday.
- In the pair (Monday, Tuesday): Tuesday appears once → favourable.
- In the pair (Tuesday, Wednesday): Tuesday appears once → favourable.
- In the other five pairs, Tuesday does not appear at all. So exactly 2 out of the 7 possible pairs contain a Tuesday.
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Probability calculation …
Method: Calendar probability by counting the "extra" days
Use this for "probability of 53 of a given weekday in a year" questions: break the year into whole weeks plus a few leftover days and reason about those leftovers.
Steps
Step 1: Split the total days into complete weeks plus a remainder.
A leap year: 366=52×7+2, so 52 full weeks (which already supply 52 of every weekday) plus 2 leftover days. A common year leaves 365=52×7+1, i.e. 1 leftover.
Step 2: List the equally likely possibilities for the leftover days.
The leftover days are consecutive. For 2 leftovers there are 7 equally likely consecutive pairs: (Sun, Mon), (Mon, Tue), …, (Sat, Sun). Enumerate them as the sample space.
Step 3: Count how many possibilities give the extra weekday you want. …
Common Mistakes
Mistake 1: Using one extra day (the common-year case) for a leap year.
Why it's wrong: a leap year has 366=52×7+2 days, so there are 2 leftover days, not 1. Correct approach: work with the 7 equally likely consecutive pairs, giving 72 (a common year would give 71).
Mistake 2: Treating the two extra days as independent single days. …
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). …
- 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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- 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-A1 markMCQQ.A bag contains (n+1) coins. It is known that one of these coins has a head on both sides, whereas the other coins are fair. One of these coins is selected at random and tossed. If the probability that the toss results in heads is 127, then the value of n is : (A) 5 (B) 3 (C) 2 (D) 4
›Reveal solutionSolution
The key idea is to treat the coin selection as a two‑case partition (two‑headed coin vs. fair coins) and apply the law of total probability. Solving the resulting equation gives n=5, so the correct option is (A).
Concept and intuition
We have a mixed bag: one trick coin that always lands heads, and n fair coins that land heads with probability 21. When we pick a coin at random and toss it, the overall chance of heads is a weighted average of the two cases. The weight for the trick coin is n+11 (since there are n+1 coins total), and for any fair coin it’s n+1n. The problem gives that overall probability as 127, so we set up an equation and solve for n.
Step‑by‑step solution
- Define the events Let T be the event that the two‑headed coin is selected, and F the event that a fair coin is selected. Since selection is random,
P(T)=n+11,P(F)=n+1n.
- Conditional probabilities for heads If the trick coin is chosen, heads is certain:
P(heads∣T)=1.
If a fair coin is chosen, the chance of heads is 21:
P(heads∣F)=21.
- Apply the law of total probability The overall probability of heads is
P(heads)=P(T)⋅P(heads∣T)+P(F)⋅P(heads∣F).
Substituting the values:
P(heads)=n+11⋅1+n+1n⋅21.
- Simplify the expression
P(heads)=n+11+2(n+1)n=2(n+1)2+n.
- Set equal to the given probability The problem states this equals 127:
- 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.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-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 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: …
- 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). …
- 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-M1 markMCQQ.A teacher has two jars of candy on her desk: Jar 1: Contains 3 Strawberry candies and 2 Orange candies. Jar 2: Contains 1 Strawberry candy and 4 Orange candies. The teacher randomly picks two candies from Jar 1 and drops them into Jar 2. Then, a student reaches into Jar 2 and picks two candies. What is the probability that the student picks two Strawberry candies? (A) 356 (B) 214 (C) 703 (D) 141
›Reveal solutionSolution
Condition on how many strawberries move from Jar 1 to Jar 2, then compute the chance of drawing two strawberries from the now 7-candy Jar 2. Total =141.
Setup. Jar 1 has 3 Strawberry (S) and 2 Orange (O). Two candies are moved into Jar 2, which started with 1 S and 4 O. After the transfer Jar 2 holds 7 candies. Let k = number of strawberries transferred.
Transfer probabilities (choosing 2 of 5 from Jar 1, (25)=10):
P(k=2)=10(23)=103,P(k=1)=10(13)(12)=106,P(k=0)=10(22)=101.
Draw two S from Jar 2 (which now has 1+k strawberries out of 7, (27)=21):
- k=2: Jar 2 has 3 S ⇒21(23)=213=71. …
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