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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 20: An Introduction to Classical Statistics (M-I-T) » L20.5 Confidence Intervals (M-I-T)

L20.5 Confidence Intervals (M-I-T)

Course:Lecture 20: An Introduction to Classical Statistics (M-I-T)
Discipline:Applied Sciences
Institute:MIT
Instructor(s): Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:Graduate

Lecture 20: An Introduction to Classical Statistics (M-I-T)

L20.10 Maximum Likelihood Estimation Examples (M-I-T)
L20.1 Lecture Overview (M-I-T)
L20.2 Overview of the Classical Statistical Framework (M-I-T)
L20.3 The Sample Mean and Some Terminology (M-I-T)
L20.4 On the Mean Squared Error of an Estimator (M-I-T)
L20.5 Confidence Intervals (M-I-T)
L20.6 Confidence Intervals for the Estimation of the Mean (M-I-T)
L20.7 Confidence Intervals for the Mean, When the Variance is Unknown (M-I-T)
L20.8 Other Natural Estimators (M-I-T)
L20.9 Maximum Likelihood Estimation (M-I-T)

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