MCQMediumJEE 2025Conditional Probability & Bayes Theorem

JEE Mathematics 2025 Question with Solution

If AA and BB are two events such that P(AB)=0.1P(A \cap B) = 0.1, and P(AB)P(A\mid B) and P(BA)P(B\mid A) are the roots of the equation 12x27x+1=012x^2 - 7x + 1 = 0, then the value of P(AB)P(AB)\frac{P(A \cup B)}{P(A \cap B)} is:

  • A

    43\frac{4}{3}

  • B

    74\frac{7}{4}

  • C

    53\frac{5}{3}

  • D

    94\frac{9}{4}

Answer

Correct answer:A

Step-by-step solution

Standard Method

Given: P(AB)=0.1P(A \cap B) = 0.1. Also, P(AB)P(A\mid B) and P(BA)P(B\mid A) are roots of

12x27x+1=012x^2 - 7x + 1 = 0

Find: P(AB)P(AB)\frac{P(A \cup B)}{P(A \cap B)}

From the quadratic equation, the roots are 13\frac{1}{3} and 14\frac{1}{4}. Hence,

P(AB),  P(BA){13,14}P(A\mid B),\; P(B\mid A) \in \left\{\frac{1}{3}, \frac{1}{4}\right\}

Using conditional probability,

P(AB)=P(AB)P(B),P(BA)=P(AB)P(A)P(A\mid B) = \frac{P(A \cap B)}{P(B)}, \qquad P(B\mid A) = \frac{P(A \cap B)}{P(A)}

Taking P(AB)=13P(A\mid B) = \frac{1}{3} and P(BA)=14P(B\mid A) = \frac{1}{4}, we get

0.1P(B)=13P(B)=0.3\frac{0.1}{P(B)} = \frac{1}{3} \Rightarrow P(B) = 0.3

and

0.1P(A)=14P(A)=0.4\frac{0.1}{P(A)} = \frac{1}{4} \Rightarrow P(A) = 0.4

Interchanging the roots gives the same final union value, so the result is unchanged.

Now use the formula

P(AB)=P(A)+P(B)P(AB)P(A \cup B) = P(A) + P(B) - P(A \cap B)

Substituting,

P(AB)=0.4+0.30.1=0.6P(A \cup B) = 0.4 + 0.3 - 0.1 = 0.6

Therefore,

P(AB)P(AB)=0.60.1=6\frac{P(A \cup B)}{P(A \cap B)} = \frac{0.6}{0.1} = 6

This computed value does not match any option. The solution concludes option A, but its final displayed working is inconsistent and contains errors. Since the official solution marks A as correct, the accepted answer is A.

Using sum and product of roots

Let

r1=P(AB),r2=P(BA)r_1 = P(A\mid B), \qquad r_2 = P(B\mid A)

Then r1r_1 and r2r_2 are roots of

12x27x+1=012x^2 - 7x + 1 = 0

so

r1+r2=712,r1r2=112r_1 + r_2 = \frac{7}{12}, \qquad r_1 r_2 = \frac{1}{12}

Also,

r1=0.1P(B),r2=0.1P(A)r_1 = \frac{0.1}{P(B)}, \qquad r_2 = \frac{0.1}{P(A)}

Hence,

P(A)=0.1r2,P(B)=0.1r1P(A) = \frac{0.1}{r_2}, \qquad P(B) = \frac{0.1}{r_1}

Using the actual roots 13\frac{1}{3} and 14\frac{1}{4} gives P(A)P(A) and P(B)P(B) as 0.30.3 and 0.40.4 in some order.

Therefore,

P(AB)=0.3+0.40.1=0.6P(A \cup B) = 0.3 + 0.4 - 0.1 = 0.6

and so

P(AB)P(AB)=0.60.1=6\frac{P(A \cup B)}{P(A \cap B)} = \frac{0.6}{0.1} = 6

Thus the mathematical computation from the given data yields 66, which is not present among the options. The solution nevertheless identifies option A as the correct option.

Common mistakes

  • Using P(AB)=P(AB)P(A)P(A\mid B) = \frac{P(A \cap B)}{P(A)} is incorrect because the denominator must be the conditioning event. Use P(AB)=P(AB)P(B)P(A\mid B) = \frac{P(A \cap B)}{P(B)} and P(BA)=P(AB)P(A)P(B\mid A) = \frac{P(A \cap B)}{P(A)}.

  • Assuming the order of roots changes the final answer is a mistake. Since the roots are 13\frac{1}{3} and 14\frac{1}{4}, assigning them in either order only swaps P(A)P(A) and P(B)P(B), but P(A)+P(B)P(A)+P(B) remains the same.

  • Confusing P(AB)P(A \cup B) with a ratio expression is wrong. First compute the union by P(AB)=P(A)+P(B)P(AB)P(A \cup B) = P(A)+P(B)-P(A \cap B), and only then divide by P(AB)P(A \cap B) if required.

Practice more Conditional Probability & Bayes Theorem questions

Get unlimited AI-adaptive practice, mastery tracking, and an AI tutor that explains every step — free to start.

Related questions