Lecture 7: Recurrences

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• ✓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

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