In this episode, we continue to dive into the linear regression model. What are the real-world applications? When our model fit is enough? What are the pros and cons of increasing complexity in our model?
We discuss also the basic principles of covariates transformation (i.e. the logarithm) and how this has played a pivotal role in the modeling of the Covid-19 epidemics.
Furthermore, we discuss how to model and interpret interactions between covariates.
In this GitHub Repository, you will find R scripts helping to understand the basics of linear regression.
