Explores autocorrelation, periodicity, and spurious correlations in time series data, emphasizing the importance of understanding underlying processes and cautioning against misinterpretation.
Delves into measuring learning effects in digital education and analytics, covering research questions, variables, experimental design, and bias solutions.
