Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.
Covers random vectors, joint probability density, independent random variables, functions of two random variables, and Gaussian random variables.
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.
