Theory of Linear Models in Biostatistics

Graduate Prerequisites: CASMA581. Linear models are essential tools for analyzing data and widely used throughout science and society. This course will focus on linear models for biology and medicine, including a review of vectors and matrices, the multivariate normal distribution and other related distributions, least squares approach, inference for general linear model, linear hypothesis testing, model diagnostics, multiple linear regression, graphical and criteria-based variable selection, prediction, regularized regression techniques and Bayesian linear models. Students will implement the theory they learn by conducting a data analysis in R, applying the concepts and techniques covered in the course to real-world biostatistical data. Effective Fall 2023, this course fulfills a single unit in the following BU Hub area: Quantitative Reasoning II, Teamwork/Collaboration.