To understand how price affects sales one idea is to model average sales as a function of price through an available dataset. This is regression, a powerful and widely used data analysis technique, and also the topic of this course. Students will learn how to use regression to analyze a variety of complex real-world problems, with the aim of understanding data and making data-informed decisions. Focus is placed on understanding the fundamental concepts and implementation issues in a programming language (R, or alternative). Topics include: (i) linear regression; (ii) model checking and selection; (iii) generalized linear models (e.g. logistic regression); (iv) time series models and forecasting; and (v) causal inference. This course emphasizes the practical applications of regression, and considers many real-world datasets and problems. Although the course used to have a substantial programming component, this year we will explore the use of AI (such as ChatGPT) to aid with code generation.
