Conditional probability is an important concept in statistics. It helps us figure out how likely something is to happen if we already know that something else has happened.

Key Points:

• What It Means: Conditional probability tells us how likely event A is to happen if event B has already happened. We write this as $P(A|B)$.

• How to Calculate It: $P(A|B) = \frac{P(A \cap B)}{P(B)}$ In this formula, $P(A \cap B)$ is the chance of both event A and event B happening together.

• Why It Matters: Understanding conditional probability helps us make better predictions. It shows us how events are related to each other, which is really helpful when we're analyzing data and making decisions.