Linearity of Expectation

Related lectures (30)

Page 2 of 3

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Covers a quiz on advanced probability concepts and calculations.

Explores conditional density, expectations, and independence of random variables with practical examples.

Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.

Introduces subgaussian and subexponential random variables, conditional expectation, and Orlicz norms.

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Explores Cheeger's inequalities for random walks on graphs and their implications.