In this talk, we introduce cluster-experiments, a Python library designed to facilitate end-to-end A/B testing workflows, including power analysis, experiment analysis, and variance reduction techniques.
python, basic stats knowledge
We will go through the main techniques for mde analysis (simulation based and using Central limit theorem), how to do variance reduction in mde analysis and how to analyse experiments with the same library.
David Masip is a Data Science Manager at Glovo. He works in AB testing, causal inference and ML, and maintains two python libraries (cluster-experiments: a library for end-2-end analysis of AB tests, including experiment design; pytest-slow-last: a pytest plugin that makes slower tests run in the end).