This lecture covers the fundamentals of regression analysis, focusing on statistical models and data analysis. Topics include linear models, normal linear models, nonlinear models, Poisson-distributed response, and failure time analysis. The instructor discusses various data sets, such as calcium uptake, smoking data, rat growth data, and spring failure data, illustrating different regression techniques and model extensions.