Lecture
This lecture covers the concepts of covariance and correlation, focusing on quantifying statistical dependence between random variables. It explains how covariance measures the linear relationship between two variables, while correlation standardizes this measure to a range between -1 and 1. The lecture also delves into the calculation of covariance and correlation coefficients, emphasizing their significance in understanding the relationship between data points. Additionally, it explores the notion of mutual information as a measure of the amount of information obtained about one random variable through another. The discussion extends to identifying coevolving sites in interacting proteins using sequence data, showcasing practical applications of these statistical concepts.