Delves into measuring learning effects in digital education and analytics, covering research questions, variables, experimental design, and bias solutions.
Covers correlation and cross-correlations in air pollution data analysis, including time series, autocorrelations, Fourier analysis, and power spectrum.
Explores variable selection through filtering and correlation methods in machine learning, emphasizing relevance quantification and relationship measurement with the label.
