Understanding Event Independence in Probability
Probability • May 2026

Understanding Event Independence in Probability

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Written By Archive Editorial
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Introduction

In probability theory, determining whether two events $A$ and $B$ are independent is a fundamental skill. Events are considered independent if the occurrence of one does not affect the probability of the other occurring.

The Mathematical Definition

Two events $A$ and $B$ are independent if and only if: $$P(A \cap B) = P(A) \times P(B)$$

Step-by-Step Problem Solving

Given:

  • $P(A) = 0.4$
  • $P(B) = 0.3$
  • $P(A \cup B) = 0.56$

Step 1: Find the intersection $P(A \cap B)$

We use the Inclusion-Exclusion Principle: $$P(A \cup B) = P(A) + P(B) - P(A \cap B)$$

Substitute the known values: $$0.56 = 0.4 + 0.3 - P(A \cap B)$$ $$0.56 = 0.7 - P(A \cap B)$$ $$P(A \cap B) = 0.7 - 0.56 = 0.14$$

Step 2: Check the independence condition

Calculate $P(A) \times P(B)$: $$0.4 \times 0.3 = 0.12$$

Compare with $P(A \cap B)$: $$0.14 \neq 0.12$$

Conclusion

Since $P(A \cap B) \neq P(A) \times P(B)$, the events $A$ and $B$ are not independent.

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