Introduction data science problems predict the what — for example, what will a house sell for? Or what will a customer purchase? Or what is the probability that a patient has a disease? Many real-world decisions, however, depend just as much on when something will happen. How long until a customer churns? When will a loan default? How much time remains before a component fails? Predicting when something will happen is a predictive modeling use case that doesn’t get much attention in introductory materials. Predicting the “when” is often referred to as time-to-event modeling or survival analysis . While event modeling shares techniques and intuitions with more traditional predictive modeling, it also introduces nuances that must be accommodated to create effective predictions. This is the start of a multi-part series that will cover the basics of time-to-event modeling. This first part will discuss basic concepts while future articles will cover time-to-event model development techniques.…