24 dersten 19. ders
Lecture 19: Conditional Probability
Dersler24 ders
- 1Lecture 1: Predicates, Sets, and Proofs
- 2Lecture 2: Contradiction and Induction
- 3Lecture 3: Casework and Strong Induction
- 4Lecture 4: State Machines
- 5Lecture 5: Sums
- 6Lecture 6: Asymptotics
- 7Lecture 7: Recurrences
- 8Lecture 8: Divisibility
- 9Lecture 9: Modular Arithmetic
- 10Lecture 10: Cryptography
- 11Lecture 11: Graphs and Coloring
- 12Lecture 12: Matching
- 13Lecture 13: Connectivity and Trees
- 14Lecture 14: Digraphs and DAGs
- 15Lecture 15: Relations and Counting
- 16Lecture 16: Counting Techniques
- 17Lecture 17: More Counting Techniques
- 18Lecture 18: Probability
- 19Lecture 19: Conditional Probability
- 20Lecture 20: Independence
- 21Lecture 21: Random Variables
- 22Lecture 22: Expectation
- 23Lecture 23: Expectation and Variance
- 24Lecture 24: Large Deviations: Chebyshev and Chernov Bound, Wrap Up