Conference Video: Melissa Santos, PhD - Time-to-Event Analysis for Non-Medical Applications
This is Melissa Santos, PhD’s Tech Talk from the WiDS Puget Sound Conference 2020. Enjoy!
ABSTRACT:
How do you estimate the time until an event, especially if the event might never happen? The statistical methods for this come from studying time from disease diagnosis to death, but we can use these methods for much more cheerful data. For example, how long does a subscription customer continue to pay you? How long does it take from someone commenting on your open-source code to becoming a contributor? How long does it take from the user being seen the first time to them becoming a paid customer? Kaplan-Meier survival curves are non-parametric estimates of the time to an event. They make no assumptions about the distribution of the time to the event, and they handle samples of various ages that may or may not have made it to the event. As well as the theory of these, we’ll dive into how to calculate them directly in SQL. To finish, I’ll share some ways we’ve been using Kaplan-Meier curves to make decisions at a Software as a Service company, especially using them to compare groups.
Melissa has been working with computers and data since 2000, in fields from security to marketing to geography. She has a PhD. in Applied Math and considers herself both a statistician and a data scientist. Currently, she is a data analyst at Pingboard, helping understand the customers and how they use the product.