| S# |
Lecture |
Course |
Institute |
Instructor |
Discipline |
| 4351 |
L13.2 Conditional Expectation as a Random Variable (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4352 |
Lecture 6.4: Quarks (M-I-T)
|
Chapter 6. Weak Interactions (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4353 |
L12.6 Covariance Properties (M-I-T)
|
Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4354 |
L13.3 The Law of Iterated Expectations (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4355 |
Lecture 7.1: Higgs Mechanism (M-I-T)
|
Chapter 7. Higgs Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4356 |
L12.7 The Variance of the Sum of Random Variables (M-I-T)
|
Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4357 |
Lecture 6.5: Neutral Current (M-I-T)
|
Chapter 6. Weak Interactions (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4358 |
Lecture 7.2: Fermion Masses (M-I-T)
|
Chapter 7. Higgs Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4359 |
L12.8 The Correlation Coefficient (M-I-T)
|
Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4360 |
L13.4 Stick-Breaking Revisited (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4361 |
Lecture 7.3: Production and Decay (M-I-T)
|
Chapter 7. Higgs Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4362 |
|
Lecture 14: Introduction to Bayesian Inference (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4363 |
L13.5 Forecast Revisions (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4364 |
L12.9 Proof of Key Properties of the Correlation Coefficient (M-I-T)
|
Lecture 12: Sum of Independent R.V.s. Covariance and Correlation (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4365 |
Lecture 7.4: Current Status (M-I-T)
|
Chapter 7. Higgs Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4366 |
L14.1 Lecture Overview (M-I-T)
|
Lecture 14: Introduction to Bayesian Inference (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4367 |
L13.6 The Conditional Variance (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4368 |
L14.2 Overview of some Application Domains (M-I-T)
|
Lecture 14: Introduction to Bayesian Inference (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4369 |
L13.7 Derivation of the Law of Total Variance (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4370 |
L14.3 Types of Inference Problems (M-I-T)
|
Lecture 14: Introduction to Bayesian Inference (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4371 |
Lecture 8.1: In the Standard Model (M-I-T)
|
Chapter 8. Neutrino Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4372 |
L13.8 A Simple Example (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4373 |
Lecture 8.2: Mass (M-I-T)
|
Chapter 8. Neutrino Physics (M-I-T)
|
MIT
|
Prof. Markus Klute
|
Basic and Health Sciences
|
| 4374 |
L14.4 The Bayesian Inference Framework (M-I-T)
|
Lecture 14: Introduction to Bayesian Inference (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
| 4375 |
L13.9 Section Means and Variances (M-I-T)
|
Lecture 13: Conditional Expectation & Variance Revisited; Sum of a Random Number of Independent R.V.s (M-I-T)
|
MIT
|
Prof. John Tsitsiklis, Prof. Patrick Jaillet
|
Applied Sciences
|
