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Worked Examples · Example 13

Q.Prove that if EE and FF are independent events, then so are the events EE and F′F'.

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The complement of an independent event remains independent of the other event. If EE and FF are independent, then P(E∩F′)=P(E)⋅P(F′)P(E \cap F') = P(E) \cdot P(F'), so EE and F′F' are independent.

The idea is simple: independence means knowing FF happened tells you nothing about EE. If that’s true, then knowing FF didn’t happen should also tell you nothing about EE. The proof just uses the complement rule and the definition of independence.


1. Start with what we know: EE and FF are independent. By definition,

P(E∩F)=P(E)⋅P(F).P(E \cap F) = P(E) \cdot P(F).

2. We want to check whether EE and F′F' are independent. That means we need to verify

P(E∩F′)=P(E)⋅P(F′).P(E \cap F') = P(E) \cdot P(F').

3. The event EE can be split into two disjoint parts: outcomes where FF happens, and outcomes where FF doesn’t happen. So

E=(E∩F)∪(E∩F′).E = (E \cap F) \cup (E \cap F').

These two pieces are mutually exclusive (they can’t both occur), so their probabilities add:

P(E)=P(E∩F)+P(E∩F′).P(E) = P(E \cap F) + P(E \cap F').

4. Rearranging gives

P(E∩F′)=P(E)−P(E∩F).P(E \cap F') = P(E) - P(E \cap F).

5. Now substitute the independence condition P(E∩F)=P(E)⋅P(F)P(E \cap F) = P(E) \cdot P(F):

P(E∩F′)=P(E)−P(E)⋅P(F)=P(E)(1−P(F)).P(E \cap F') = P(E) - P(E) \cdot P(F) = P(E) \bigl(1 - P(F)\bigr).

6. But 1−P(F)1 - P(F) is exactly P(F′)P(F') (the complement rule). So

P(E∩F′)=P(E)⋅P(F′).P(E \cap F') = P(E) \cdot P(F'). …

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