Search Results

Linear regression and associated techniques are some of the most tested and trusted methods in data science and statistics. In this course, we will develop the skills to apply linear methods to investigate relationships between various types of data, visualize data, and consider the responsible use of such models. Topics may include linear and multiple regression, resampling, model and feature selection, representing analyzed data visually, logistic regression, and the data science life cycle. Python/R will be used throughout. Prerequisites: : MA 162, MA 202, MA 214, CS 106, DS 101.