Regression: Linear Models

This lecture covers the fundamentals of regression, focusing on linear models, generalized linear models, and mixed-effect models. It explains the concept of regression, model fitting, parameter estimation, and model evaluation. The lecture also delves into the interpretation of regression results, the impact of input variables, and the limitations of linear models. Practical examples and use cases are discussed, including time series prediction and the importance of handling correlated samples.