400013 SE Introduction to regression models (2024W)

This course offers a practical and applied introduction to ordinary least squares (OLS) regression models, one of the most widely-used statistical methods in the social sciences. This course will help you to construct, interpret, and critically evaluate OLS regression models. You will have a firm understanding of the assumptions of the model, the differences between various types of independent variables, and how to identify and address potential issues in regression models. You will also be able to critically evaluate OLS models used in scholarly journals.
We will begin by reviewing basic statistical concepts, such as comparing means and testing hypotheses, before moving on to the analysis of the association between two continuous variables. We will then discuss simple linear regression and the assumptions underlying OLS regression. The course will proceed to cover multiple regression models, with a focus on the practical interpretation of results. Different types of explanatory variables, including binary/nominal variables and interaction effects, will be introduced. Finally, an overview of possible problems and their remedies is provided, and we will consider how to approach model-building in OLS regression.
Throughout the course, real-world examples are used to illustrate concepts and ensure practical understanding.