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Electrical Engineering and Computer Science (M-I-T)
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Introduction to Probability (Spring 2018) (M-I-T)
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Part II: Inference & Limit Theorems (M-I-T)
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Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
(7 Lectures Available)
S#
Lecture
Course
Institute
Instructor
Discipline
1
L19.1 Lecture Overview (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
2
L19.2 The Central Limit Theorem (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
3
L19.3 Discussion of the CLT (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
4
L19.4 Illustration of the CLT (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
5
L19.5 CLT Examples (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
6
L19.6 Normal Approximation to the Binomial (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Applied Sciences
7
L19.7 Polling Revisited (M-I-T)
Lecture 19: The Central Limit Theorem (CLT) (M-I-T)
MIT
Prof. John Tsitsiklis, Prof. Patrick Jaillet
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