Explains estimation, correlation, and Pearson correlation in statistics, focusing on measuring and describing relationships between variables.
Explores the panel effect model with fixed and random effects, discussing estimation challenges and the impact of serial correlation.
Explores the Extended Kalman Predictor algorithm and the linearized Kalman Filter for multivariable control systems, discussing the challenges and applications.
Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.
Explores dependence in random vectors, covering joint density, conditional independence, covariance, and moment generating functions.
