Generalizations to Sub- & Supermartingales

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

Page 3 of 4

Martingale Convergence

Explores martingale convergence, discussing the conditions for convergence and variance in martingales.

Martingale Theory: Basics and Applications

Covers the basics of Martingale theory and its applications in random variables.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Random Variables and Expected Value

Introduces random variables, probability distributions, and expected values through practical examples.

Independence and Covariance

Explores independence and covariance between random variables, discussing their implications and calculation methods.

Central Limit Theorem

Covers the Central Limit Theorem and its application to random variables, proving convergence to a normal distribution.

Central Limit Theorem: Properties and Applications

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.

Statistical Theory: Fundamentals

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

Transformations of Random Variables

Covers the pdf of the sum of continuous random variables, convolution, and transformations like Y=aX.

Stochastic Models for Communications

Explores mean, variance, probability functions, inequalities, and various types of random variables, including Binomial, Geometric, Poisson, and Gaussian distributions.