Covers correlation and cross-correlations in air pollution data analysis, including time series, autocorrelations, Fourier analysis, and power spectrum.
Explains estimation, correlation, and Pearson correlation in statistics, focusing on measuring and describing relationships between variables.
Explores signal processing fundamentals, including discrete time signals, spectral factorization, and stochastic processes.
Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.
