Diving into survival analysis with Python — a statistical branch used to predict and calculate the expected duration of time for one or more events.

Author(s): Pratik Shukla

This article covers an extensive review with step-by-step explanations and code for how to perform statistical survival analysis used to investigate the time some event takes to occur, such as patient survival during the COVID-19 pandemic, the time to failure of engineering products, or even the time to closing a sale after an initial customer contact.

This tutorial’s code is available on Github and its full implementation on Google Colab.

📚 Check out our Monte Carlo Simulation Tutorial with Python 📚

Table of Contents:

1. Survival Analysis Basics
2. Kaplan-Meier fitter Theory with an Example.
3. Nelson-Aalen fitter Theory with an Example.
4. Kaplan-Meier fitter Based on Different Groups.
5. Log-Rank-Test with an Example.
6. Cox-Regression with an Example.
7. Resources.

#mathematics #machine-learning #survival-analysis #statistics #python