Independent Events

Learn what independent events are in probability, how to identify them, their properties, and how to compute probabilities when two events do not affect each other.

1. Meaning of Independent Events

Two events are called independent if the occurrence of one does not affect the occurrence of the other. In simple terms, knowing that one event has happened gives no information about the other.

Examples of independent situations:

  • Tossing a coin and rolling a die.
  • Drawing a card from a deck, replacing it, and then drawing again.
  • Choosing a person from one group and a person from another group.

2. Definition of Independent Events

Events A and B are independent if:

\( P(A|B) = P(A) \)

and

\( P(B|A) = P(B) \)

This means that knowing B happened does not change the chance of A, and vice versa.

3. Multiplication Rule for Independent Events

For independent events, the multiplication rule becomes:

\( P(A \cap B) = P(A)P(B) \)

This formula gives the probability that both events happen together.

3.1. Example

Consider the events:

  • A: getting a head on a coin → 1/2
  • B: getting a 3 on a die → 1/6

Since the events do not affect each other:

\( P(A \cap B) = (1/2)(1/6) = 1/12 \)

4. Examples of Independent Events

Here are some simple examples to understand independence better:

4.1. Coin and Dice Example

Tossing a coin and rolling a die are independent because the coin result does not influence the die number.

4.2. Cards With Replacement

Drawing a card, replacing it back into the deck, and then drawing again creates independent events because the deck returns to its original state.

4.3. Two Separate Bags

Picking a ball from Bag A and then picking a ball from Bag B forms independent events, since the two bags do not interact.

5. When Events Are Not Independent

Events are not independent (they are dependent) when one affects the other. For example:

  • Drawing two cards without replacement — the first draw affects the second.
  • Choosing students from the same group — the first choice changes who is left.

In such cases, independence does not hold and conditional probability must be used instead.