Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
Covers the Metropolis-Hastings algorithm and gradient-based approaches for biasing searches towards higher likelihood values.
Explores filtering signals with a moving average filter and the process of sampling, emphasizing the importance of signal reconstruction from samples.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
