Dependence (Statistical) Formula
The Formula
When to use: Knowing A happened tells you something about B—they're connected.
Quick Example
Notation
What This Formula Means
When the probability of one event changes based on whether another event occurred.
Knowing A happened tells you something about B—they're connected.
Formal View
Worked Examples
Example 1
mediumSolution
- 1 Event A = first ball is red: P(A) = \frac{5}{8}
- 2 Event B = second ball is red, given first was red: P(B|A) = \frac{4}{7} (only 4 red left among 7)
- 3 Apply multiplication rule: P(A \cap B) = P(A) \cdot P(B|A) = \frac{5}{8} \times \frac{4}{7} = \frac{20}{56} = \frac{5}{14}
- 4 Note: events are dependent because removing the first ball changes the composition of the bag
Answer
Example 2
hardCommon Mistakes
- Assuming all sequential events are dependent — coin flips remain independent even if done one after another
- Confusing dependence with causation — rain and umbrellas are statistically dependent but rain does not cause umbrellas to exist
- Using the multiplication rule P(A) \times P(B) for dependent events, forgetting to use P(A) \times P(B|A)
Why This Formula Matters
Most real-world events are dependent—ignoring this leads to wrong calculations.
Frequently Asked Questions
What is the Dependence (Statistical) formula?
When the probability of one event changes based on whether another event occurred.
How do you use the Dependence (Statistical) formula?
Knowing A happened tells you something about B—they're connected.
What do the symbols mean in the Dependence (Statistical) formula?
P(B|A) \neq P(B) indicates that A and B are dependent
Why is the Dependence (Statistical) formula important in Math?
Most real-world events are dependent—ignoring this leads to wrong calculations.
What do students get wrong about Dependence (Statistical)?
Dependence \neq causation. Rain and umbrellas are dependent but rain doesn't cause umbrellas.
What should I learn before the Dependence (Statistical) formula?
Before studying the Dependence (Statistical) formula, you should understand: probability, independent events.