Why Logistic Regression should be the last thing you learn when becoming a Data Scientist

There are hundred of types of logistic regression, some for categorical variables, some with curious names such as Poisson regression. It is confusing for the expert, and even more for the beginner, and for your boss. If you transform your response (often a proportion or a binary response such as fraud or no fraud in this context) you can instead use a linear regression. While purists claim that an actual logistic regression is more precise (from a theoretical perspective), model precision is irrelevant: it is the quality of your data that matters. A model with 1% extra accuracy does not help if your data has 20% of noise, or your theoretical model is a rough approximation of the reality.