| 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
|
