Quantifying Statistical Dependence

This lecture continues the discussion on maximum likelihood applications, focusing on quantifying statistical dependence. Topics covered include covariance, correlation, mutual information, and identifying coevolving sites in interacting proteins using sequence data. The lecture also delves into inferring probability distributions from data, model selection, parameter estimation, maximum entropy inference, and predicting protein structure from sequence data.