Skip to content
Question

Q.Let E and F be two events such that P(E)=0.1P(E) = 0.1, P(F)=0.3P(F) = 0.3, P(E∪F)=0.4P(E \cup F) = 0.4, then P(F ∣ E)P(F\,|\,E) is: (A) 0.60.6 (B) 0.40.4 (C) 0.50.5 (D) 00

CBSECBSE Class XII Board 2024MCQ· 1mImportance★★★★★
🔒 Locked · start free trial →

You're viewing a preview — the full solution, concept, methods & PYQ mapping are locked.

Start your 14-day free trial to unlock the full solution →

To find the conditional probability P(F ∣ E)P(F\,|\,E), we first determine the probability of the intersection P(E∩F)P(E \cap F) using the Addition Rule, and then divide by P(E)P(E). The events E and F are mutually exclusive, leading to P(E∩F)=0P(E \cap F) = 0, so P(F ∣ E)=0P(F\,|\,E) = \boxed{0}.

When we talk about P(F ∣ E)P(F\,|\,E), we are asking for the probability that event F occurs, given that event E has already occurred. This is called conditional probability. The key idea here is that the sample space for event F is no longer the entire original sample space, but rather it is restricted to only those outcomes where event E has happened.

The formula for conditional probability is:

P(F ∣ E)=P(F∩E)P(E)P(F\,|\,E) = \frac{P(F \cap E)}{P(E)}

This formula tells us that the probability of F given E is the probability of both F and E happening, divided by the probability of E happening. We need to find P(F∩E)P(F \cap E) first, as P(E)P(E) is already given.

Let's break down the solution step-by-step.

  1. Identify Given Information and What's Needed:

    We are given:

    • P(E)=0.1P(E) = 0.1
    • P(F)=0.3P(F) = 0.3
    • P(E∪F)=0.4P(E \cup F) = 0.4

    We need to find P(F ∣ E)P(F\,|\,E). To use the conditional probability formula, we require P(F∩E)P(F \cap E) and P(E)P(E). We already have P(E)P(E).

  2. Find the Probability of the Intersection, P(E∩F)P(E \cap F):

    We can use the Addition Rule for probabilities, which relates the probabilities of the union, individual events, and their intersection:

P(E∪F)=P(E)+P(F)−P(E∩F)P(E \cup F) = P(E) + P(F) - P(E \cap F)

We can rearrange this formula to solve for $P(E \cap F)$:

P(E∩F)=P(E)+P(F)−P(E∪F)P(E \cap F) = P(E) + P(F) - P(E \cup F)

Now, substitute the given values:

P(E∩F)=0.1+0.3−0.4P(E \cap F) = 0.1 + 0.3 - 0.4

P(E∩F)=0.4−0.4P(E \cap F) = 0.4 - 0.4

$$P(E \cap F) = 0$$ …

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.