Independent vs. Dependent Events
By the end of this lesson, you’ll be able to:
- Identify whether events are independent or dependent.
- Compute probabilities correctly for each type.
- Understand how replacement affects independence.
- Recognize dependence in real-world contexts.
Key Ideas
Independent Events
One event does not affect the other.
\[
P(A\ \text{and}\ B) = P(A)P(B)
\]
Dependent Events
First event changes the probability of the second.
\[
P(A\ \text{and}\ B) = P(A)\cdot P(B\mid A)
\]
Common Problem Types
Testing for Independence
Ask: “Does the first event change the probability of the second?”
Example:
Two coin flips → independent.
Card Draws With and Without Replacement
Replacement → independent
No replacement → dependent
Example:
\(P(\text{ace then ace without replacement}) = (4/52)(3/51)\).
Selecting People or Objects From a Group
Choosing without putting them back typically creates dependence.
Example:
Choosing team captains without replacement.
Situations Where Probabilities Change
Weather, conditional statements, conditional tables.
Example:
\(P(\text{rain tomorrow} \mid \text{rain today})\) differs from \(P(\text{rain tomorrow})\).
Probability Trees for Dependent Events
Tree diagrams show conditional probabilities clearly.
Strategies
- Ask if the second event’s probability changes after the first.
- Identify whether replacement occurs.
- For dependent events, write conditional probability explicitly.
- Use trees if multiple conditional branches.
Worked Examples
Example 1
Choosing two marbles without replacement from a bag of 5 red, 3 blue.
\(P(\text{red then blue}) = (5/8)(3/7)\).
Example 2
Two independent coin flips:
\(P(\text{heads then tails}) = (1/2)(1/2)=1/4\).
- Treating dependent events as independent.
- Forgetting to update totals after removing items.
- Thinking independence = mutually exclusive (they’re different!).
- Ignoring conditional probabilities.
Practice Problems
- Two coin flips: independent or dependent?
- Draw 2 cards with replacement: \(P(\text{two queens})\)?
- Draw 2 cards without replacement: \(P(\text{both black})\)?
- Choose 2 students from 30 without replacement: dependent?
- Independent
- \((4/52)(4/52)=1/169\)
- \((26/52)(25/51)=25/102\)
- Yes, dependent (group size changes).
Summary
- Independent: one event does not affect the other.
- Dependent: the first event changes the second.
- Replacement restores independence.
- Ask: “Does the first event change the next?”
- Replacement → independent.
- Use tree diagrams for conditional probabilities.