Probability 1
Offered By: Ryan O'Donnell via YouTube
Course Description
Overview
Dive into the foundations of probability theory and its applications in computer science through this comprehensive lecture from the "Great Theoretical Ideas in Computer Science" series. Explore key concepts such as events, probabilities, conditioning, and the Chain Rule while tracing the historical roots of probability to 17th century France. Engage with practical examples, including the intriguing Silver and Gold problem, and uncover the secret "Principle of Independence" that underpins many probabilistic analyses. Enhance your understanding of how to analyze random code and tackle trickier probability problems in this informative 78-minute session.
Syllabus
15-251: Great Theoretical Ideas in Computer Science Lecture 17
How to Analyze Random Code
Events and Probabilities: Facts
France, 1654
Conditioning: formally
Chain Rule
Silver and Gold: a problem
Example
Trickier Problem
Independence Problem
The Secret "Principle of Independence"
Taught by
Ryan O'Donnell
Related Courses
Introduction to Statistics: ProbabilityUniversity of California, Berkeley via edX Aléatoire : une introduction aux probabilités - Partie 1
École Polytechnique via Coursera Einführung in die Wahrscheinlichkeitstheorie
Johannes Gutenberg University Mainz via iversity Combinatorics and Probability
Moscow Institute of Physics and Technology via Coursera Probability
University of Pennsylvania via Coursera