Q.If $P(A) = \frac{7}{13}$, $P(B) = \frac{9}{13}$ and $P(A \cap B) = \frac{4}{13}$, evaluate $P(A|B)$.

Showing the 12 most recent of 69 on this concept.

1. AP EAPCET 2021Set eng-2021-08-23-FN1 markMCQ
   Q.Let $A$ and $B$ be two events with $P(A) = \dfrac{1}{7}$, $P(A/B) = \dfrac{2}{5}$ and $P(B) = \dfrac{2}{7}$. Then the value $P(B/A)$ is (A) $\dfrac{1}{5}$ (B) $\dfrac{5}{49}$ (C) $\dfrac{4}{5}$ (D) $\dfrac{3}{5}$

   ›Reveal solutionSolution

   Chain the conditional-probability definition twice: first get $P(A\cap B)$ from $P(A/B)$, then get $P(B/A)$ from that.

   Concept and Intuition

   Conditional probability is defined as $P(E/F)=\dfrac{P(E\cap F)}{P(F)}$. Given one conditional probability, we can back out the joint probability $P(A\cap B)$, and then use it (with the definition again, but conditioning the other way) to find the other conditional probability.

   Step-by-Step Solution

   1. $P(A/B) = \dfrac{P(A\cap B)}{P(B)} \Rightarrow P(A\cap B) = P(A/B)\cdot P(B) = \dfrac{2}{5}\times\dfrac{2}{7} = \dfrac{4}{35}$.
   2. Now use $P(B/A) = \dfrac{P(A\cap B)}{P(A)} = \dfrac{4/35}{1/7}$.
   3. Dividing by $1/7$ is the same as multiplying by $7$: $\dfrac{4}{35}\times 7 = \dfrac{28}{35} = \dfrac{4}{5}$.

   Common Mistakes

   • Mixing up which probability ($P(A)$ or $P(B)$) belongs in the denominator at each step — always match the given event in the conditioning.
   • Forgetting to simplify $28/35$ to $4/5$.

   ✓Final answer

   The correct option is (C) — $\dfrac{4}{5}$.

   ANSWER: C

2. AP EAPCET 2021Set eng-2021-08-25-AN1 markMCQ
   Q.Given $P(A) = 0.5, P(B) = 0.4, P(A \cap B) = 0.3$ then $P(A'/B')$ is equal to (A) $\dfrac{1}{3}$ (B) $\dfrac{1}{2}$ (C) $\dfrac{2}{3}$ (D) $\dfrac{3}{4}$

   ›Reveal solutionSolution

   Using De Morgan's law $A'\cap B'=(A\cup B)'$ and the conditional probability formula gives $P(A'|B')=\dfrac23$.

   Concept and Intuition

   $P(A'|B')$ asks: given we're outside $B$, what's the chance we're also outside $A$? The key trick is that $A'\cap B' = (A\cup B)'$ (De Morgan), which is easy to compute from $P(A\cup B)$.

   Step-by-Step Solution

   1. $P(A\cup B)=P(A)+P(B)-P(A\cap B)=0.5+0.4-0.3=0.6$.
   2. $P(A'\cap B')=P((A\cup B)')=1-P(A\cup B)=1-0.6=0.4$.
   3. $P(B')=1-P(B)=1-0.4=0.6$.
   4. $P(A'|B')=\dfrac{P(A'\cap B')}{P(B')}=\dfrac{0.4}{0.6}=\dfrac23$.

   Common Mistakes

   • Trying to compute $P(A'\cap B')$ directly instead of via De Morgan's law and the union probability, leading to more error-prone arithmetic.

   ✓Final answer

   The correct option is (C) — $\dfrac23$.

   ANSWER: C

3. AP EAPCET 2021Set eng-2021-08-24-FN1 markMCQ
   Q.If $A$ and $B$ are mutually exclusive events with $P(A) = \dfrac{1}{4}$ and $P(B) = \dfrac{3}{7}$. Then what is the value of $P(A / A \cup B) =$ (A) $\dfrac{7}{19}$ (B) $\dfrac{12}{19}$ (C) $\dfrac{06}{19}$ (D) $\dfrac{13}{19}$

   ›Reveal solutionSolution

   Mutually exclusive events make $P(A\cup B)$ a simple sum, and since $A$ is entirely contained in $A\cup B$, the conditional probability reduces to $P(A)/P(A\cup B)$.

   Concept and Intuition

   For mutually exclusive $A,B$: $P(A\cap B)=0$, so $P(A\cup B)=P(A)+P(B)$. Also $A\cap(A\cup B)=A$ always, so $P(A\mid A\cup B)=\dfrac{P(A\cap(A\cup B))}{P(A\cup B)}=\dfrac{P(A)}{P(A\cup B)}$.

   Step-by-Step Solution

   1. $P(A\cup B) = P(A)+P(B) = \dfrac14+\dfrac37$.
   2. Common denominator 28: $\dfrac{7}{28}+\dfrac{12}{28}=\dfrac{19}{28}$.
   3. $P(A\mid A\cup B) = \dfrac{P(A)}{P(A\cup B)} = \dfrac{1/4}{19/28} = \dfrac14\times\dfrac{28}{19} = \dfrac{7}{19}$.

   Common Mistakes

   • Adding probabilities incorrectly by using the wrong common denominator.
   • Forgetting that mutual exclusivity is what allows $P(A\cup B)=P(A)+P(B)$ (no overlap term to subtract).

   ✓Final answer

   The correct option is (A) — $\dfrac{7}{19}$.

   ANSWER: A

4. AP EAPCET 2024Set eng-2024-05-23-FN1 markMCQ
   Q.It is given that in a random experiment events A and B are such that $P(A) = \dfrac{1}{4}$, $P(A|B) = \dfrac{1}{2}$ and $P(B|A) = \dfrac{2}{3}$ then $P(B) =$ (A) $\dfrac{1}{3}$ (B) $\dfrac{2}{3}$ (C) $\dfrac{1}{2}$ (D) $\dfrac{1}{6}$

   ›Reveal solutionSolution

   Using $P(B|A)$ to find $P(A\cap B)$, then dividing by $P(A|B)$, gives $P(B)=\dfrac13$.

   Concept and Intuition

   The conditional probability definitions $P(A|B)=\dfrac{P(A\cap B)}{P(B)}$ and $P(B|A)=\dfrac{P(A\cap B)}{P(A)}$ share the common quantity $P(A\cap B)$ — computing it from one equation lets us solve the other for the unknown probability.

   Step-by-Step Solution

   1. From $P(B|A)=\dfrac{P(A\cap B)}{P(A)}=\dfrac23$, and $P(A)=\dfrac14$: $P(A\cap B)=\dfrac23\times\dfrac14=\dfrac16$.
   2. From $P(A|B)=\dfrac{P(A\cap B)}{P(B)}=\dfrac12$: $P(B)=\dfrac{P(A\cap B)}{P(A|B)}=\dfrac{1/6}{1/2}=\dfrac13$.

   Common Mistakes

   • Confusing which conditional probability to use to find $P(A\cap B)$ first (must use the one whose conditioning event's total probability, $P(A)$, is already known).
   • Dividing instead of multiplying (or vice versa) when rearranging the conditional probability formula.

   ✓Final answer

   The correct option is (A) — $\dfrac13$.

   ANSWER: A

5. AP EAPCET 2025Set eng-2025-05-27-FN1 markMCQ
   Q.On every evening, a student either watches TV or reads a book. The probability of watching TV is $\dfrac{4}{5}$. If he watches TV, the probability that he will fall asleep is $\dfrac{3}{4}$ and it is $\dfrac{1}{4}$ when he reads a book. If the student is found to be asleep on an evening, the probability that he watched the TV is (A) $\dfrac{11}{13}$ (B) $\dfrac{12}{13}$ (C) $\dfrac{2}{13}$ (D) $\dfrac{4}{13}$

   ›Reveal solutionSolution

   This tests Bayes' theorem: finding the probability of a cause (watched TV) given an observed effect (fell asleep). The answer is $\dfrac{12}{13}$.

   Concept and Intuition

   When asked "given the observed outcome, what's the probability of a particular cause," that's a Bayes'-theorem setup: compute the joint probability of that cause with the outcome, and divide by the total probability of the outcome (summed over all causes).

   Step-by-Step Solution

   1. $P(\text{TV})=\tfrac45$, $P(\text{book})=\tfrac15$.
   2. $P(\text{asleep}\mid\text{TV})=\tfrac34$, $P(\text{asleep}\mid\text{book})=\tfrac14$.
   3. Total probability of falling asleep: $P(\text{asleep})=P(\text{TV})P(\text{asleep}\mid\text{TV})+P(\text{book})P(\text{asleep}\mid\text{book})=\tfrac45\cdot\tfrac34+\tfrac15\cdot\tfrac14=\tfrac35+\tfrac1{20}=\tfrac{12}{20}+\tfrac1{20}=\tfrac{13}{20}$.
   4. By Bayes' theorem: $P(\text{TV}\mid\text{asleep})=\dfrac{P(\text{TV})P(\text{asleep}\mid\text{TV})}{P(\text{asleep})}=\dfrac{\tfrac35}{\tfrac{13}{20}}=\tfrac35\times\tfrac{20}{13}=\tfrac{60}{65}=\tfrac{12}{13}$.

   Common Mistakes

   • Reporting the joint probability $P(\text{TV})P(\text{asleep}\mid\text{TV})=\tfrac35$ as the final answer instead of dividing by $P(\text{asleep})$.
   • Arithmetic slip converting $\tfrac35$ and $\tfrac1{20}$ to a common denominator.

   ✓Final answer

   The correct option is (B) — $\dfrac{12}{13}$.

   ANSWER: B

6. AP EAPCET 2025Set eng-2025-05-26-FN1 markMCQ
   Q.If two events A and B are such that $P(\bar A)=0.3$, $P(B)=0.4$ and $P(A\cap\bar B)=0.5$, then $P(B/(A\cup\bar B))=$ (A) 0.25 (B) 0.6 (C) 0.45 (D) 0.8

   ›Reveal solutionSolution

   This tests careful set manipulation of conditional probability with a compound conditioning event $A\cup\bar B$. Answer: 0.25.

   Concept and Intuition

   Conditional probability $P(B\mid E) = \dfrac{P(B\cap E)}{P(E)}$ works exactly the same way when $E$ is a compound event like $A\cup\bar B$ — we just need to correctly compute $P(E)$ and $P(B\cap E)$ using set algebra (distributing intersection over union, and using the fact that $B$ and $\bar B$ are disjoint).

   Step-by-Step Solution

   1. From $P(\bar A)=0.3$, get $P(A)=1-0.3=0.7$.
   2. $P(A\cap\bar B)=0.5$ is given directly, so $P(A\cap B)=P(A)-P(A\cap\bar B)=0.7-0.5=0.2$.
   3. Compute $P(A\cup\bar B)$ using inclusion-exclusion: $P(A\cup\bar B)=P(A)+P(\bar B)-P(A\cap\bar B)$. Here $P(\bar B)=1-0.4=0.6$, so $P(A\cup\bar B)=0.7+0.6-0.5=0.8$.
   4. Compute the numerator $P\big(B\cap(A\cup\bar B)\big)$: distributing, $B\cap(A\cup\bar B)=(B\cap A)\cup(B\cap\bar B)$. Since $B\cap\bar B=\varnothing$, this simplifies to just $A\cap B$, with probability $0.2$.
   5. Therefore $P(B\mid A\cup\bar B)=\dfrac{0.2}{0.8}=0.25$.

   Common Mistakes

   • Forgetting that $B\cap\bar B$ is empty and mistakenly adding an extra term.
   • Using $P(A\cap B)$ directly as $P(B)-P(A\cap \bar B)$ instead of $P(A)-P(A\cap\bar B)$.

   ✓Final answer

   The correct option is (A) — 0.25.

   ANSWER: A

7. AP EAPCET 2022Set eng-2022-07-06-FN1 markMCQ
   Q.If E and F are events such that $P(\bar{F}) = 0.7$ and $P(E \cap F) = 0.2$, then $P(E|F)$ is (A) $2/3$ (B) $1/3$ (C) $3/4$ (D) $1/4$

   ›Reveal solutionSolution

   This tests the basic conditional-probability formula together with the complement rule. $P(E|F)=2/3$.

   Concept and Intuition

   $P(E|F)$ asks: given that $F$ has already happened, what fraction of that reduced sample space does $E\cap F$ occupy? It is always $\dfrac{P(E\cap F)}{P(F)}$, so first we need $P(F)$ itself, which is given indirectly through its complement.

   Step-by-Step Solution

   1. $P(\bar F) = 0.7 \Rightarrow P(F) = 1 - 0.7 = 0.3$.
   2. $P(E\cap F) = 0.2$ is given directly.
   3. $P(E|F) = \dfrac{P(E\cap F)}{P(F)} = \dfrac{0.2}{0.3} = \dfrac{2}{3}$.

   Common Mistakes

   • Forgetting to convert $P(\bar F)$ to $P(F)$ and dividing by $0.7$ instead of $0.3$.
   • Confusing $P(E|F)$ with $P(F|E)$, which would need $P(E)$ instead.

   ✓Final answer

   The correct option is (A) — $2/3$.

   ANSWER: A

8. AP EAPCET 2026Set eng-2026-05-13-FN1 markMCQ
   Q.Bag A contains 3 white and 4 black balls. Bag B contains 4 white and 3 black balls. Bag C contains 2 white and 5 black balls. A bag is randomly selected and then a ball is randomly drawn from that bag. If the ball drawn was found to be white, then the probability that the ball is drawn from bag C is (A) $\dfrac{1}{6}$ (B) $\dfrac{2}{9}$ (C) $\dfrac{1}{4}$ (D) $\dfrac{2}{13}$

   ›Reveal solutionSolution

   This is a direct Bayes'-theorem (inverse probability) question. Answer: $\dfrac{2}{9}$.

   Concept and Intuition

   We're given the outcome (a white ball was drawn) and asked for the probability of a particular cause (it came from bag C). This is exactly Bayes' theorem: $P(C\mid W) = \dfrac{P(C)P(W\mid C)}{\sum_i P(\text{bag}_i)P(W\mid \text{bag}_i)}$.

   Step-by-Step Solution

   1. Each bag is chosen with probability $\frac13$.
   2. $P(W\mid A) = \dfrac{3}{7}$ (3 white out of 7 total in bag A).
   3. $P(W\mid B) = \dfrac{4}{7}$ (4 white out of 7 in bag B).
   4. $P(W\mid C) = \dfrac{2}{7}$ (2 white out of 7 in bag C).
   5. Total probability of white: $P(W) = \frac13\left(\dfrac37+\dfrac47+\dfrac27\right) = \frac13\cdot\dfrac{9}{7} = \dfrac{9}{21} = \dfrac{3}{7}$.
   6. By Bayes' theorem: $P(C\mid W) = \dfrac{\frac13\cdot\frac27}{\frac37} = \dfrac{\frac{2}{21}}{\frac37} = \dfrac{2}{21}\times\dfrac{7}{3} = \dfrac{14}{63} = \dfrac{2}{9}$.

   Common Mistakes

   • Forgetting to divide by the total probability $P(W)$ and stopping at the numerator $\frac{2}{21}$.
   • Mixing up which bag's white-ball fraction goes with which term.

   ✓Final answer

   The correct option is (B) — $\dfrac{2}{9}$.

   ANSWER: B

9. AP EAPCET 2026Set eng-2026-05-18-FN1 markMCQ
   Q.Two balls are drawn at random from a box containing 4 white, 6 black balls one after the other without replacement. If it is known that second ball drawn is black, then the probability that the first ball drawn is also black is (A) $\dfrac{5}{11}$ (B) $\dfrac{5}{9}$ (C) $\dfrac{5}{12}$ (D) $\dfrac{5}{13}$

   ›Reveal solutionSolution

   Conditional probability with sampling without replacement, solved with Bayes' theorem; answer is $\frac{5}{9}$.

   Concept and Intuition

   When balls are drawn one after another without replacement, the marginal probability that any particular draw (say the 2nd) is black equals the overall proportion of black balls, $\frac{6}{10}$ — position doesn't matter for the marginal event by symmetry. To find the conditional probability of the first draw given information about the second, we use Bayes' theorem: we need the joint probability of both events and divide by the marginal probability of the conditioning event.

   Step-by-Step Solution

   1. Total balls: 4 white (W) + 6 black (B) = 10.
   2. $P(\text{2nd is black}) = P(\text{1st B, 2nd B}) + P(\text{1st W, 2nd B})$ $= \frac{6}{10}\cdot\frac{5}{9} + \frac{4}{10}\cdot\frac{6}{9} = \frac{30}{90}+\frac{24}{90} = \frac{54}{90} = \frac{3}{5}$.
   3. $P(\text{1st black and 2nd black}) = \frac{6}{10}\cdot\frac{5}{9} = \frac{30}{90} = \frac{1}{3}$.
   4. By Bayes' theorem: $P(\text{1st black}\mid \text{2nd black}) = \dfrac{P(\text{1st B, 2nd B})}{P(\text{2nd B})} = \dfrac{1/3}{3/5} = \dfrac{5}{9}$.

   Common Mistakes

   • Assuming $P(\text{2nd black}) = \frac{5}{9}$ (the conditional probability given 1st was black) instead of computing the correct marginal $\frac{3}{5}$.
   • Forgetting to include both cases (1st W/2nd B and 1st B/2nd B) when finding the joint denominator event.

   ✓Final answer

   The correct option is (B) — $\dfrac{5}{9}$.

   ANSWER: B

10. AP EAPCET 2022Set eng-2022-07-06-FN1 markMCQ
    Q.Two persons P and Q are considering to apply for a job. The probability that P applies for the job is 1/4, the probability that P applies for the job given that Q applies for the job is 1/2, and the probability that Q applies for the job given that P applies for the job is 1/3. Then the probability that P does not apply for the job given that Q does not apply for the job is (A) $4/5$ (B) $5/6$ (C) $7/8$ (D) $11/12$

    ›Reveal solutionSolution

    Chain the given conditional probabilities to find $P(Q)$ and $P(P\cap Q)$, then use the complement rule — the answer is (A) $4/5$.

    Concept and Intuition

    Conditional probability definitions let us cross-multiply to recover the joint probability $P(P\cap Q)$ from either conditional. Once $P(P), P(Q), P(P\cap Q)$ are all known, De Morgan's law converts "neither event" into the complement of the union.

    Step-by-Step Solution

    1. Given: $P(P)=\tfrac14$, $P(P|Q)=\tfrac12$, $P(Q|P)=\tfrac13$.
    2. $P(P\cap Q) = P(Q|P)\cdot P(P) = \tfrac13\times\tfrac14 = \tfrac1{12}$.
    3. Also $P(P\cap Q) = P(P|Q)\cdot P(Q) \Rightarrow \tfrac1{12} = \tfrac12\cdot P(Q) \Rightarrow P(Q)=\tfrac16$.
    4. $P(P\cup Q) = P(P)+P(Q)-P(P\cap Q) = \tfrac14+\tfrac16-\tfrac1{12} = \tfrac{3}{12}+\tfrac{2}{12}-\tfrac{1}{12}=\tfrac{4}{12}=\tfrac13$.
    5. By De Morgan's law, "neither P nor Q applies" is the complement of $P\cup Q$: $P(\overline P\cap\overline Q) = 1-\tfrac13=\tfrac23$.
    6. $P(\overline Q) = 1-P(Q) = 1-\tfrac16=\tfrac56$.
    7. $P(\overline P|\overline Q) = \dfrac{P(\overline P\cap\overline Q)}{P(\overline Q)} = \dfrac{2/3}{5/6} = \dfrac23\times\dfrac65 = \dfrac{12}{15}=\dfrac45$.

    Common Mistakes

    • Mixing up which conditional probability to use for computing the joint probability first (must use $P(Q|P)P(P)$, not $P(P|Q)P(P)$, to directly match given data).
    • Forgetting to convert to complements at the final step (computing $P(P|Q)$-type instead of $P(\overline P|\overline Q)$).

    ✓Final answer

    The correct option is (A) — $4/5$.

    ANSWER: A

11. AP EAPCET 2023Set eng-2023-05-18-AN1 markMCQ
    Q.If A,B are any two events of a random experiment and $P(B)\neq1$, then $P(A\mid B^c)=$ (A) $\dfrac{P(A)+P(A\cap B)}{1-P(B)}$ (B) $\dfrac{P(A)-P(A\cap B)}{1-P(B)}$ (C) $\dfrac{P(A)+P(A\cap B)}{1+P(B)}$ (D) $\dfrac{P(A)}{1+P(B)}$

    ›Reveal solutionSolution

    Direct application of the conditional-probability definition to the complement event gives $P(A\mid B^c)=\dfrac{P(A)-P(A\cap B)}{1-P(B)}$.

    Concept and Intuition

    $A\cap B^c$ is exactly the part of $A$ that does not overlap with $B$, so its probability is $P(A)$ minus the overlapping piece $P(A\cap B)$. Dividing by $P(B^c)=1-P(B)$ (valid since $P(B)\ne1$) gives the conditional probability.

    Step-by-Step Solution

    1. $P(A\mid B^c)=\dfrac{P(A\cap B^c)}{P(B^c)}$ by definition (needs $P(B^c)\ne0$, i.e. $P(B)\ne1$, as given).
    2. $A=(A\cap B)\cup(A\cap B^c)$, a disjoint union, so $P(A)=P(A\cap B)+P(A\cap B^c)\Rightarrow P(A\cap B^c)=P(A)-P(A\cap B)$.
    3. $P(B^c)=1-P(B)$.
    4. Combine: $P(A\mid B^c)=\dfrac{P(A)-P(A\cap B)}{1-P(B)}$.

    Common Mistakes

    • Writing $P(A\cap B^c)=P(A)+P(A\cap B)$ instead of subtracting — a very common sign slip.
    • Forgetting the denominator must be $P(B^c)=1-P(B)$, not $1+P(B)$.

    ✓Final answer

    The correct option is (B) — $\dfrac{P(A)-P(A\cap B)}{1-P(B)}$.

    ANSWER: B

12. AP EAPCET 2022Set eng-2022-07-05-FN1 markMCQ
    Q.If A and B are two events such that $P(B) \neq 0$ and $P(B) \neq 1$, then $P(\bar{A}|\bar{B})$ is (A) $1-P(A|B)$ (B) $1-P(\bar{A}|B)$ (C) $\frac{1-P(A\cup B)}{P(\bar{B})}$ (D) $\frac{P(\bar{A})}{P(\bar{B})}$

    ›Reveal solutionSolution

    Directly apply the definition of conditional probability together with De Morgan's law; the answer is $\frac{1-P(A\cup B)}{P(\bar B)}$.

    Concept and Intuition

    Conditional probability is defined as $P(X|Y)=\dfrac{P(X\cap Y)}{P(Y)}$. Here $X=\bar A$, $Y=\bar B$. By De Morgan's law, $\bar A\cap\bar B = \overline{A\cup B}$, so its probability is $1-P(A\cup B)$.

    Step-by-Step Solution

    1. $P(\bar A|\bar B)=\dfrac{P(\bar A\cap\bar B)}{P(\bar B)}$.
    2. $\bar A\cap\bar B=\overline{A\cup B}$ (De Morgan).
    3. So $P(\bar A\cap\bar B)=1-P(A\cup B)$.
    4. Substituting: $P(\bar A|\bar B)=\dfrac{1-P(A\cup B)}{P(\bar B)}$.

    Common Mistakes

    • Confusing $\bar A\cap\bar B$ with $\overline{A\cap B}$ — these are different sets; De Morgan swaps union and intersection under complementation.

    ✓Final answer

    The correct option is (C) — $\dfrac{1-P(A\cup B)}{P(\bar B)}$.

    ANSWER: C