Probability & Statistics
GradesAlgebra II & TrigonometryProbability & StatisticsConditional Probability & Independence

Conditional Probability & Independence

🎲 Probability & Statistics
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Conditional Probability & Independence

Compute conditional probabilities and determine whether events are independent.

The conditional probability P(A | B) is the probability of event A given that event B has already occurred. It narrows the sample space to only those outcomes where B occurs.

P(AB)=P(AB)P(B)(P(B)>0)P(A \mid B) = \frac{P(A \cap B)}{P(B)} \quad (P(B) > 0)
Events A and B are independent iff: P(AB)=P(A)    P(AB)=P(A)P(B)\text{Events A and B are independent iff: } P(A \mid B) = P(A) \iff P(A \cap B) = P(A)\cdot P(B)

Independent Events

P(A|B) = P(A)P(A∩B) = P(A)·P(B)Knowledge of B gives no info about AExample: flipping two separate coins

Dependent Events

P(A|B) ≠ P(A)P(A∩B) ≠ P(A)·P(B)Knowledge of B changes probability of AExample: drawing cards without replacement

Always test independence by checking if P(A∩B) = P(A)·P(B).

🃏Drawing Cards Without Replacement
Deck of 52. P(King on 2nd draw | King on 1st draw) = 3/51 = 1/17, since only 3 kings remain from 51 cards. Compare to P(King) = 4/52 = 1/13 — different, so the events are dependent.
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Remember This!

For independent events, "with replacement" sampling ensures each draw is independent. "Without replacement" creates dependent events because the sample space changes.

✏️ Try It!

P(A) = 0.4, P(B) = 0.5, P(A∩B) = 0.2. Are A and B independent?

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