Q.An unbiased die is thrown twice. Let the event A be 'odd number on the first throw' and B the event 'odd number on the second throw'. Check the independence of the events A and B.
Concept understanding — Event Independence
Event Independence
Two events are independent when the occurrence of one does not change the probability of the other. Toss a coin and roll a die: the coin landing heads tells you nothing about whether the die shows a six. Contrast this with drawing cards without replacement, where the first draw does change the odds for the second — those events are dependent.
From Conditional Probability to a Clean Test
"Knowing B doesn't change A" means P(A∣B)=P(A). Substituting the definition P(A∣B)=P(B)P(A∩B) and clearing the fraction gives the symmetric form used in practice:
P(A∩B)=P(A)P(B).
Events A and B are independent exactly when the probability of both occurring equals the product of their individual probabilities. This version is preferred because it needs no non-zero condition and treats A and B alike.
A Quick Check
Roll a fair die. Let A={2,4,6} (even) and B={4,5,6} (greater than 3). Then P(A)=P(B)=21, and A∩B={4,6} so P(A∩B)=31. Since 31=21⋅21=41, these events are not independent.
Three or More Events
Events A,B,C are mutually independent only if all four conditions hold: the three pairwise products and
P(A∩B∩C)=P(A)P(B)P(C).
Pairwise independence alone is not enough to guarantee mutual independence.
Independent is not the same as mutually exclusive. Mutually exclusive events (with A∩B=∅) of non-zero probability are in fact strongly dependent: if one occurs the other cannot, so knowing one drastically changes the other's probability.
When events are independent, the multiplication rule simplifies to P(A∩B)=P(A)P(B), and it extends to any number of independent events. This is exactly what powers the binomial distribution and all repeated-trial problems.
The multiplication rule for independent events, P(A∩B) = P(A)P(B), is a core definition in the NCERT Class 12 Probability chapter and a near-guaranteed CBSE board and JEE Main question. "Independent events vs mutually exclusive events" is one of the most frequently searched probability confusions, and this distinction is tested almost every year in some form.
Concept: Event Independence — Two events are independent if P(A∩B)=P(A)⋅P(B).
Step 1: For a fair die, each throw has 3 odd numbers out of 6.
P(A)=63=21, and P(B)=21.
Step 2: The event A∩B means odd on both throws. There are 3×3=9 favourable outcomes out of 6×6=36 total.
P(A∩B)=369=41.
Step 3: Check the product: P(A)⋅P(B)=21×21=41.
Since P(A∩B)=P(A)⋅P(B), the events are independent.
The events A and B are independent.
For two throws of a fair die, event A (first throw odd) and event B (second throw odd) are independent because the outcome of the first throw does not influence the second. We verify this by showing P(A∩B)=P(A)⋅P(B)=41.
Why Independence Matters Here
When we say two events are independent, we mean that knowing whether one event happened gives you no information about whether the other event happened. In the context of throwing a die twice, the result of the first throw has absolutely no effect on the second throw — the die has no memory. So intuitively, A and B should be independent.
But intuition isn't proof. We need to check the mathematical definition: two events A and B are independent if and only if P(A∩B)=P(A)⋅P(B).
Let's work through it step by step.
1. Find P(A) — probability of odd number on the first throw
A fair die has six faces: 1, 2, 3, 4, 5, 6. The odd numbers are 1, 3, 5 — three outcomes out of six.
P(A)=63=21
2. Find P(B) — probability of odd number on the second throw
Exactly the same reasoning applies to the second throw. The second throw is independent of the first by the nature of the experiment.
P(B)=63=21
3. Find P(A∩B) — probability that both throws show odd numbers
The sample space for two throws has 6×6=36 equally likely outcomes. For both throws to be odd, the first throw must be one of {1, 3, 5} and the second must also be one of {1, 3, 5}. That gives 3×3=9 favourable outcomes.
P(A∩B)=369=41
You can also think of this as: the probability that the first is odd is 21, and given that, the probability the second is odd is still 21 (since they're independent by design). So P(A∩B)=21×21=41 — but this already assumes independence, so it's a shortcut, not a proof.
4. Check the independence condition
Now compute P(A)⋅P(B):
P(A)⋅P(B)=21×21=41
Compare with P(A∩B)=41. They are equal.
A common mistake is to think that because two events can happen together, they must be dependent. That's not true. Independence is about the ratio of probabilities, not just whether the intersection is non-zero. Here, the intersection is non-empty (9 outcomes), yet the events are independent.
5. Conclusion
Since P(A∩B)=P(A)⋅P(B), the events A and B satisfy the definition of independence.
The events A and B are independent, as P(A∩B)=41=P(A)⋅P(B).
Method: Testing independence of events tied to different trials
Use this when two events refer to different repetitions of an experiment (first throw vs second throw) and you must verify independence formally rather than assert it.
Steps
Step 1: Find each marginal probability.
Compute P(A) and P(B) from a single trial's outcomes (e.g. "odd on a throw" is 63=21).
Step 2: Find the joint probability from the full two-trial space.
Count favourable ordered outcomes over the total (6×6=36 for two dice): both-odd gives 3×3=9, so P(A∩B)=369=41. Get this from the sample space, not by assuming independence.
Step 3: Check the product rule.
Verify P(A∩B)=P(A)P(B). Deriving the joint by multiplying already assumes the result, so for a genuine proof you must obtain P(A∩B) independently (by counting) and then confirm the equality holds.
Common Mistakes
Mistake 1: Assuming independence and multiplying 21×21 as the "proof."
Why it's wrong: writing P(A∩B)=P(A)P(B) from the start assumes exactly what must be proven. Correct approach: obtain P(A∩B)=369=41 by counting the 36-outcome space independently, then confirm it equals the product.
Mistake 2: Thinking a non-empty intersection implies dependence.
Why it's wrong: independence is a numerical condition, not about whether the events can co-occur. Correct approach: rely solely on P(A∩B)=P(A)P(B).
- COMEDK 2025Set 2025-E1 markMCQQ.An unbiased die is tossed twice. What is the probability of getting a 4,5 or 6 on the first toss and a 1,2,3 or 4 on the second toss? (A) 65 (B) 43 (C) 32 (D) 31
›Reveal solutionSolution
The probability is the product of the probabilities of two independent events: first toss gives {4,5,6} (3 outcomes out of 6) and second toss gives {1,2,3,4} (4 outcomes out of 6). Multiplying gives 63×64=3612=31, so the answer is (D).
Concept and intuition
When two events are independent — meaning the outcome of the first doesn’t affect the second — the probability that both happen is simply the product of their individual probabilities. Here, each toss of a fair die is independent, so we can treat the two conditions separately and multiply.
- First toss condition We want a 4, 5, or 6. That’s 3 favorable outcomes out of 6 equally likely faces.
P(first in {4,5,6})=63=21.
- Second toss condition We want a 1, 2, 3, or 4. That’s 4 favorable outcomes out of 6.
P(second in {1,2,3,4})=64=32.
- Combine using independence Since the two tosses are independent,
P(both conditions)=21×32=62=31.
TipA common shortcut: count total favorable ordered pairs. First toss has 3 choices, second has 4 choices → 3×4=12 favorable outcomes. Total possible ordered pairs: 6×6=36. So probability is 3612=31.
Watch outA classic mistake is to think the second condition includes 4, so it overlaps with the first condition — but since the tosses are independent, overlap doesn’t matter. You multiply, not add.
✓Final answerThe correct option is (D).
ANSWER: D
- COMEDK 2024Set 2024-A1 markMCQQ.A and B are two independent events. The probability of their simultaneous occurrence is 81 and the probability that neither of them occurs is 83. Then their individual probabilities are (A) 83 and 81 (B) 85 and 41 (C) 43 and 21 (D) 21 and 41
›Reveal solutionSolution
Using the independence condition P(A∩B)=P(A)P(B)=81 and the complement condition P(Ac∩Bc)=(1−P(A))(1−P(B))=83, we solve a quadratic to find P(A)=21 and P(B)=41 (or vice versa), matching option (D).
We are told that A and B are independent events. This is the key that unlocks the problem: for independent events, the probability of both occurring is simply the product of their individual probabilities. We are also given the probability that neither occurs — that is, the complement of their union. Let’s denote p=P(A) and q=P(B). Our goal is to find p and q.
1. Translate the given information into equations
- Simultaneous occurrence: P(A∩B)=81. Because A and B are independent,
P(A∩B)=P(A)⋅P(B)=pq=81.
- Neither occurs: P(neither A nor B)=P(Ac∩Bc)=83. For independent events, the complements are also independent, so
P(Ac∩Bc)=(1−p)(1−q)=83.
So we have the system:
{pq=81(1−p)(1−q)=83
2. Expand the second equation
(1−p)(1−q)=1−p−q+pq=83.
Substitute pq=81:
1−p−q+81=83.
Simplify:
1+81−83=p+q⇒1−82=p+q⇒1−41=p+q.
Thus:
p+q=43.
3. Solve for p and q
We now have:
p+q=43,pq=81.
These are the sum and product of the roots of a quadratic equation. The numbers p and q satisfy:
x2−(p+q)x+pq=0⇒x2−43x+81=0.
Multiply through by 8 to clear denominators:
8x2−6x+1=0.
Factor or use the quadratic formula:
x=166±36−32=166±2.
So:
x=168=21orx=164=41.
Thus the two probabilities are 21 and 41 (in either order).
4. Check against the options
Option (D) lists 21 and 41, which matches exactly.
TipA quick sanity check: if p=21 and q=41, then pq=81 and (1−p)(1−q)=21⋅43=83. Both conditions hold perfectly.
Watch outA common mistake is to forget that “neither occurs” is the complement of the union, not just 1−P(A∪B) incorrectly computed. Always use (1−p)(1−q) for independent events — it’s simpler and avoids errors.
✓Final answerThe correct option is (D).
ANSWER: D
- COMEDK 2021Set 2021-B1 markMCQQ.If A and B be independent events with P(A)=41 and P(A∪B)=2P(B)−P(A) then P(B) = (A) 2/5 (B) 1/4 (C) 3/5 (D) 2/3
›Reveal solutionSolution
P(B)=52.
For independent A,B: P(A∪B)=P(A)+P(B)−P(A)P(B)=41+P(B)−41P(B).
Given P(A∪B)=2P(B)−P(A)=2P(B)−41. Equate:
41+P(B)−41P(B)=2P(B)−41.
21=2P(B)−P(B)+41P(B)=45P(B)⟹P(B)=52.
✓Final answerThe correct option is (A) — 2/5
- KCET 2022Set C-41 markMCQQ.If A and B are two independent events such that P(A)=0.75, P(A∪B)=0.65, and P(B)=x, then find the value of x: (A) 8/15 (B) 9/14 (C) 7/15 (D) 5/14
›Reveal solutionSolution
Use P(A∪B)=P(A)+P(B)−P(A)P(B) for independent events and solve the resulting linear equation for x, giving x=8/15.
Step 1 — The concept: addition rule + independence
The general addition rule is
P(A∪B)=P(A)+P(B)−P(A∩B)
When A and B are independent, the occurrence of one does not change the chance of the other, so
P(A∩B)=P(A)P(B)
Combining the two:
P(A∪B)=P(A)+P(B)−P(A)P(B)
With P(B)=x this becomes a single linear equation in x:
P(A∪B)=P(A)+x(1−P(A))
Step 2 — A necessary consistency check on the data
Because A⊆A∪B, we must always have P(A∪B)≥P(A). The stem prints P(A)=0.75 and P(A∪B)=0.65, i.e. P(A∪B)<P(A) — impossible. Solving with those numbers confirms it:
0.65=0.75+x(1−0.75)⇒0.25x=−0.10⇒x=−0.4
a negative probability, which cannot be. So P(A) must read 0.25 (the value consistent with P(A∪B)=0.65) — and, as Step 3 shows, 0.25 is precisely the value that reproduces one of the printed options exactly.
Step 3 — Solve
With P(A)=0.25, P(A∪B)=0.65, P(B)=x:
0.65=0.25+x−(0.25)x
0.65−0.25=x(1−0.25)
0.40=0.75x
x=0.750.40=7540=158
Step 4 — Verify
P(B)=8/15≈0.5333 (a legitimate probability). Check:
P(A∪B)=0.25+0.5333−(0.25)(0.5333)=0.7833−0.1333=0.65✓
None of the other options reproduces 0.65 from any sensible value of P(A), so 8/15 is the unique consistent answer.
✓Final answerThe correct option is (A) — 8/15, verified by two experienced subject lecturers.
ANSWER: A
- KCET 2025Set A-11 markMCQQ.Consider the following statements. Statement (I): If E and F are two independent events, then E' and F' are also independent. Statement (II): Two mutually exclusive events with non-zero probabilities of occurrence cannot be independent. Which of the following is correct? (A) Statement (I) is true and statement (II) is false (B) Statement (I) is false and statement (II) is true (C) Both the statements are true (D) Both the statements are false
›Reveal solutionSolution
Prove Statement (I) with De Morgan + the addition rule, and Statement (II) by showing P(E∩F)=0 contradicts P(E)P(F)>0 — both come out true.
Step 1 — Verify Statement (I): if E and F are independent, so are E′ and F′.
Given independence: P(E∩F)=P(E)P(F).
Use De Morgan's law, E′∩F′=(E∪F)′:
P(E′∩F′)=1−P(E∪F)
Apply the addition theorem, then the independence hypothesis:
=1−[P(E)+P(F)−P(E∩F)]
=1−P(E)−P(F)+P(E)P(F)
Now factor by grouping:
=[1−P(E)]−P(F)[1−P(E)]=[1−P(E)][1−P(F)]
=P(E′)P(F′)
Since P(E′∩F′)=P(E′)P(F′), the complements E′ and F′ are independent.
⇒ Statement (I) is TRUE.
(Intuition: independence means knowing whether E happened tells you nothing about F. Knowing whether E didn't happen is the same information, so it still tells you nothing about F — or about F not happening.)
Step 2 — Verify Statement (II): two mutually exclusive events with non-zero probabilities cannot be independent.
Suppose E and F are mutually exclusive with P(E)>0 and P(F)>0.
Mutually exclusive means they cannot occur together:
E∩F=ϕ⟹P(E∩F)=0
But independence would require
P(E∩F)=P(E)P(F)>0(a product of two positive numbers)
These cannot both hold: 0= a positive number. Contradiction. Hence such events can never be independent.
⇒ Statement (II) is TRUE.
(Intuition: mutual exclusivity is the strongest possible dependence — if E occurs you know for certain that F did not, i.e. P(F∣E)=0=P(F). Far from being unrelated, the events are maximally informative about each other.)
Step 3 — Conclude. Both statements are true, which is option (C).
✓Final answerThe correct option is (C) — Both the statements are true.
ANSWER: C
- COMEDK 2025Set 2025-A1 markMCQQ.In a kabaddi league, two matches are being played between Jaipur and Delhi. It is assumed that the outcomes of the two games are independent. The probability of Jaipur winning, drawing and losing the game against Delhi are 21,103 and 51 respectively. Each team gets 5 points for win, 3 points for draw and 0 points for loss in a game. After two games, find the probability that Jaipur has more points than Delhi. (A) 41 (B) 203 (C) 2011 (D) 52
›Reveal solutionSolution
The key idea is to list all possible outcomes of the two independent matches, compute the total points for Jaipur and Delhi in each case, and sum the probabilities where Jaipur’s total exceeds Delhi’s. The result is 2011, which corresponds to option (C).
We are told the outcomes of the two matches are independent. For each match, the probabilities are:
- Jaipur wins: 21
- Draw: 103
- Jaipur loses: 51
Points per match: win = 5, draw = 3, loss = 0.
We need the probability that after two matches, Jaipur’s total points are strictly greater than Delhi’s.
Concept and intuition:
Since each match gives points to both teams simultaneously, we can think of the difference in points per match.
- If Jaipur wins: Jaipur +5, Delhi +0 → difference = +5 for Jaipur.
- If draw: both get +3 → difference = 0.
- If Jaipur loses: Jaipur +0, Delhi +5 → difference = –5 for Jaipur.
After two matches, the total difference is the sum of the two per-match differences. Jaipur has more points if and only if this total difference is positive.
Because the matches are independent, we can list all 3×3 = 9 possible pairs of outcomes, compute the total difference, and sum probabilities where it is > 0.
Step-by-step solution:
-
List all possible outcomes for the two matches.
Let the outcomes be (result of match 1, result of match 2). Each result can be W (Jaipur win), D (draw), or L (Jaipur loss).
The probability of each pair is the product of the individual probabilities (independence).
-
Compute the point difference for each match:
- W: difference = +5
- D: difference = 0
- L: difference = –5
After two matches, total difference = sum of the two differences.
-
Enumerate all 9 cases and find where total difference > 0:
Match 1 Match 2 Diff 1 Diff 2 Total diff Jaipur > Delhi? W W +5 +5 +10 Yes W D +5 0 +5 Yes W L +5 –5 0 No D W 0 +5 +5 Yes D D 0 0 0 No D L 0 –5 –5 No L W –5 +5 0 No L D –5 0 –5 No L L –5 –5 –10 No Only the first three rows (W,W), (W,D), (D,W) give Jaipur strictly more points.
-
Compute probabilities for these favorable cases:
- P(W,W) = 21×21=41
- P(W,D) = 21×103=203
- P(D,W) = 103×21=203
-
Sum them:
41+203+203=205+203+203=2011
TipNotice that the cases where total difference = 0 (W,L), (L,W), (D,D) do not count because we need strictly more points. A common mistake is to include draws in the total.
Watch outDo not forget that (W,L) and (L,W) give a net difference of 0, not a win for Jaipur. Also, the order matters because matches are distinct (first and second), so (W,D) and (D,W) are separate outcomes.
✓Final answerThe correct option is (C).
ANSWER: C
- COMEDK 2026Set 2026-M1 markMCQQ.The odds against Arjun solving a problem are 5:2 and the odds in favour of Bhavana solving the same problem are 3:4. What is the probability that the problem is NOT solved by either of them? (A) 4910 (B) 4929 (C) 4920 (D) 4915
›Reveal solutionSolution
Convert odds to probabilities, then use the multiplication rule for independent events: the probability neither solves is the product of their individual failure probabilities, giving 4920.
Concept & Intuition
Odds are a different way of expressing probability. "Odds against Arjun" means the ratio of failure to success; "odds in favour of Bhavana" means the ratio of success to failure. To find the probability that neither solves the problem, we first convert each person's odds into a probability of failure, then multiply them — assuming their attempts are independent.
-
Convert Arjun's odds to probability
Odds against Arjun = 5:2 means for every 5 failures, there are 2 successes.
Total outcomes = 5+2=7.
Probability Arjun fails = 75.
Probability Arjun succeeds = 72.
-
Convert Bhavana's odds to probability
Odds in favour of Bhavana = 3:4 means for every 3 successes, there are 4 failures.
Total outcomes = 3+4=7.
Probability Bhavana fails = 74.
Probability Bhavana succeeds = 73.
-
Probability neither solves
The problem is not solved by either only if both fail. Assuming independence:
P(neither solves)=P(Arjun fails)×P(Bhavana fails)=75×74=4920.
Watch outA common mistake is to treat odds as probabilities directly. Odds of 5:2 against does not mean probability 25 or 75 for success — it's 75 for failure.
TipRemember:
- "Odds against" = P(success)P(fail)
- "Odds in favour" = P(fail)P(success) Always convert to probabilities by summing the two numbers.
✓Final answerThe correct option is (C).
ANSWER: C
-
🎓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.