Modern Regression Analysis in R

This course will provide a foundational set of statistical modeling tools for data science. Specifically, students will be introduced to the methods, theory, and applications of linear statistical models, covering the topics of parameter estimation, residual diagnostics, fairness, and various strategies for variable selection and model comparison. It will also cover the misuse of statistical models and the ethical implications of such misuse. This course can be taken for academic credit toward CU Boulder’s Master of Science in Data Science (MS-DS) program, offered on Coursera. The MS-DS is an interdisciplinary degree that includes faculty from CU Boulder’s Departments of Applied Mathematics, Computer Science, Information Science, and other departments. The MS-DS program, which is outcome-based and requires no application, is ideal for individuals with a broad educational background and/or professional experience in computer science, computer science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder Logo adapted from a photo by Vincent Ledvina on Unsplash