For the full-time sections on Wednesday, the faculty member plans to deliver the lectures in person. Tuesday's evening section will be fully remote.
To understand how price affects sales one idea is to model average sales as a function of price. 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 predicting future events. Focus is placed on understanding of fundamental concepts and implementation issues in a programming language (R, or alternative). Real-world examples are used throughout to illustrate application of the techniques. Topics covered include: (i) linear regression; (ii) multiple linear regression; (iii) model checking and selection; (iv) generalized linear models (e.g. logistic regression); (v) time series models and forecasting; (vi) causal inference. This course emphasizes the practical applications of regression, and so it has a heavy programming component applied on a diverse set of real-world examples.