Why and How to Model Conditional Variance, with an Application to my Letterboxd Data

One of the main assumptions of linear regression taught in statistics courses is that of “constant variance” or “homoscedasticity.” Having data that do not have constant variance (i.e., are heteroscedastic) is then often treated as a problem—a nuisance that violates our assumptions and, among other things, produces inaccurate …