SCCI Digital Library and Forum
Menu
Home
About Us
Video Library
eBooks
SCCI Forum
Home
»
Applied Sciences
»
Engineering
»
Electrical Engineering and Computer Science (M-I-T)
»
Introduction to Probability (Spring 2018) (M-I-T)
»
Part I: The Fundamentals (M-I-T)
»
Lecture 2: Conditioning and Bayes' Rule (M-I-T)
»
L02.1 Lecture Overview (M-I-T)
L02.1 Lecture Overview (M-I-T)
Course:
Lecture 2: Conditioning and Bayes' Rule (M-I-T)
Discipline:
Applied Sciences
Institute:
MIT
Instructor(s):
Prof. John Tsitsiklis, Prof. Patrick Jaillet
Level:
Graduate
Lecture 2: Conditioning and Bayes' Rule (M-I-T)
L02.1 Lecture Overview (M-I-T)
L02.2 Conditional Probabilities (M-I-T)
L02.3 A Die Roll Example (M-I-T)
L02.4 Conditional Probabilities Obey the Same Axioms (M-I-T)
L02.5 A Radar Example and Three Basic Tools (M-I-T)
L02.6 The Multiplication Rule (M-I-T)
L02.7 Total Probability Theorem (M-I-T)
L02.8 Bayes' Rule (M-I-T)