Login to filter by course Login to filter by course Reset
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Covers inequalities, joint Gaussian distribution, risk estimation, and classification method testing in probability and statistics.
Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.
Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.
Covers copulas, Sklar's Theorem, meta distributions, and various dependence measures like rank correlations and coefficients of tail dependence.
