Covers correlation and cross-correlations in air pollution data analysis, including time series, autocorrelations, Fourier analysis, and power spectrum.
Explores autocorrelation, periodicity, and spurious correlations in time series data, emphasizing the importance of understanding underlying processes and cautioning against misinterpretation.
Explores the distinction between Eulerian and Lagrangian descriptions of fluid flow through velocity field concepts and different types of lines visualization.
