You learned how to calculate probabilities using sample spaces, events, and the fundamental formula P(A) = favorable / total.
You can now apply the complement rule, addition rule, and multiplication rule. You understand independent versus dependent events and conditional probability.
You computed expected values and saw how probability applies to randomized algorithms, hash collisions, and weighted random selection.
These tools give you a foundation for analyzing algorithms with randomness and uncertainty. Next section builds on this.