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Home » Applied Sciences » Engineering » Electrical Engineering and Computer Science (M-I-T) » Introduction to Probability (Spring 2018) (M-I-T) » Part II: Inference & Limit Theorems (M-I-T) » Lecture 18: Inequalities, Convergence, and the Weak Law of Large Numbers (M-I-T) » L18.1 Lecture Overview (M-I-T)

L18.1 Lecture Overview (M-I-T)

Course:Lecture 18: Inequalities, Convergence, and the Weak Law of Large Numbers (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:Graduate

Lecture 18: Inequalities, Convergence, and the Weak Law of Large Numbers (M-I-T)

L18.1 Lecture Overview (M-I-T)
L18.2 The Markov Inequality (M-I-T)
L18.3 The Chebyshev Inequality (M-I-T)
L18.4 The Weak Law of Large Numbers (M-I-T)
L18.5 Polling (M-I-T)
L18.6 Convergence in Probability (M-I-T)
L18.7 Convergence in Probability Examples (M-I-T)
L18.8 Related Topics (M-I-T)
S18.1 Convergence in Probability of the Sum of Two Random Variables (M-I-T)
S18.2 Jensen's Inequality (M-I-T)
S18.3 Hoeffding's Inequality (M-I-T)

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