This lecture delves into the mathematics behind parametric models, focusing on statistical estimation, maximum-likelihood estimators, regression models, and model selection. It covers topics such as Gaussian linear regression, logistic regression, Poisson regression, and the application of parametric models in various fields like MRI imaging and disease detection.