Workshop: An Introduction to Bayesian Statistics and Buy-Till-You-Die Models

For 2022, we are starting a series of workshops to introduce the concept of Bayesian statistics using a practical real-world problem: building customer analytics models to help predict customer behaviour.

All code for my workshops and talks can be found in this GitHub repo:

https://github.com/kaybenleroll/data_workshops

This workshop is contained in the ws_clvbayes_202201/ folder

This series of workshops is done live, with code being commited and pushed to the above GitHub repository as well as the Dockerfile infrastructure to build the container to run the code.

Bayesian statistics is an approach that enables the combination of domain knowledge, data and statistical modelling in a principled and logical way. The primary outputs of these models are distributions of the model parameters that allows us to quantify the uncertainty in our models.

In the fourth workshop of this series we continue our work on building frequency models, expanding into the role of using hierarchical models to use 'partial pooling' to improve our model fits. Time permitting, we will then turn our attention to looking at working on obtaining statistical estimates of the distribution of customer lifetimes.

We strive to make our workshops as standalone as possible, so new attendees are always welcome!

This workshop will be broadcast using Zoom and will be recorded and made available online via our YouTube channel.