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Q.Let EE be an event of a sample space SS of an experiment, then P(S∣E)=P(S \mid E) = (A) P(S∩E)P(S \cap E) (B) P(E)P(E) (C) 11 (D) 00

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Conditional probability P(S∣E)P(S \mid E) asks: given that event EE has occurred, what is the probability that the entire sample space SS occurs? Since SS always contains every outcome, the answer is always 11.

Concept & Intuition

The notation P(S∣E)P(S \mid E) means the probability of the sample space SS happening, under the condition that event EE has already occurred. The sample space SS is the set of all possible outcomes of the experiment — it is the "universe" we are working in. No matter what event EE we condition on, EE itself is a subset of SS. So if EE happens, every outcome that occurs is still inside SS. In other words, SS is guaranteed to happen regardless of any condition. The conditional probability of a certain event (an event that always occurs) is always 11.

The formal definition of conditional probability is:

P(A∣B)=P(A∩B)P(B)provided P(B)>0.P(A \mid B) = \frac{P(A \cap B)}{P(B)} \quad \text{provided } P(B) > 0.

Here A=SA = S and B=EB = E. Since SS is the entire sample space, S∩E=ES \cap E = E (because every outcome in EE is also in SS). So the numerator becomes P(E)P(E), and the denominator is also P(E)P(E). The ratio is 11 as long as P(E)>0P(E) > 0.

Watch out

A common mistake is to think P(S∣E)P(S \mid E) equals P(S∩E)P(S \cap E) or P(E)P(E). But P(S∣E)P(S \mid E) is a conditional probability, not a joint or marginal probability. Always apply the definition: P(A∣B)=P(A∩B)/P(B)P(A \mid B) = P(A \cap B) / P(B).

Step-by-step solution

  1. Recall the definition of conditional probability. For any two events AA and BB with P(B)>0P(B) > 0,

P(A∣B)=P(A∩B)P(B).P(A \mid B) = \frac{P(A \cap B)}{P(B)}.

  1. Identify AA and BB in this problem. Here A=SA = S (the sample space) and B=EB = E (the given event). So P(S∣E)=P(S∩E)P(E).P(S \mid E) = \frac{P(S \cap E)}{P(E)}. …

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