25 episodes

Video Lectures from 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010

# Probabilistic Systems Analysis and Applied Probability MIT

• Education

Video Lectures from 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010

• video
Lecture 1: Probability Models and Axioms

## Lecture 1: Probability Models and Axioms

In this lecture, the professor discussed probability as a mathematical framework, probabilistic models, axioms of probability, and gave some simple examples.

• 51 min
• video
Lecture 2: Conditioning and Bayes' Rule

## Lecture 2: Conditioning and Bayes' Rule

In this lecture, the professor discussed conditional probability, multiplication rule, total probability theorem, and Bayes' rule.

• 51 min
• video
Lecture 3: Independence

## Lecture 3: Independence

In this lecture, the professor discussed independence of two events, independence of a collection of events, and independence vs. pairwise independence.

• 46 min
• video
Lecture 4: Counting

## Lecture 4: Counting

In this lecture, the professor discussed principles of counting, permutations, combinations, partitions, and binomial probabilities.

• 51 min
• video
Lecture 5: Discrete Random Variables I

## Lecture 5: Discrete Random Variables I

In this lecture, the professor discussed random variables, probability mass function, expectation, and variance.

• 50 min
• video
Lecture 6: Discrete Random Variables II

## Lecture 6: Discrete Random Variables II

In this lecture, the professor discussed conditional PMF, geometric PMF, total expectation theorem, and joint PMF of two random variables.

• 50 min