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

(10 Lectures Available)

S# Lecture Course Institute Instructor Discipline
1
  • L20.10 Maximum Likelihood Estimation Examples (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
2
  • L20.1 Lecture Overview (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
3
  • L20.2 Overview of the Classical Statistical Framework (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
4
  • L20.3 The Sample Mean and Some Terminology (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
5
  • L20.4 On the Mean Squared Error of an Estimator (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
6
  • L20.5 Confidence Intervals (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
7
  • L20.6 Confidence Intervals for the Estimation of the Mean (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
8
  • L20.7 Confidence Intervals for the Mean, When the Variance is Unknown (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
9
  • L20.8 Other Natural Estimators (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences
10
  • L20.9 Maximum Likelihood Estimation (M-I-T)
Lecture 20: An Introduction to Classical Statistics (M-I-T) MIT Prof. John Tsitsiklis, Prof. Patrick Jaillet Applied Sciences

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