Lecture
Variance of Random Variables
Related lectures (51)
Stochastic Processes: Review and PropertiesMOOC: Advanced statistical physics
Covers the review of random variables, probability density functions, variance, and Gaussian processes.
Probability Theory: Random Variables and Covariance
Covers random variables, covariance, and joint probability distributions.
Probability and Statistics
Covers probability distributions, moments, and continuous random variables.
Elements of Statistics: Probability and Random Variables
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Probability Density Function: Basics
Covers the basics of Probability Density Function (PDF) in probability theory.
Dependence and Correlation
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Joint Distributions
Explores joint distributions, marginal laws, covariance, correlation, and variance properties.
Optimization and Simulation
Introduces the Metropolis-Hastings algorithm for efficient simulation of random variables with given probabilities.
Modes of Convergence of Random Variables
Covers the modes of convergence of random variables and the Central Limit Theorem, discussing implications and approximations.
Continuous Random Variables: Basics
Explores continuous random variables, cdf, pdf, convolution, and sum of dice.