Regression Discontinuity Design you own this product

prerequisites
basics of Python • basics of data science
skills learned
spot discontinuities in data • use RDD techniques to estimate the impact of discount on profits
Matheus Facure
1 week · 4-6 hours per week · INTERMEDIATE

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Look inside

In this liveProject, you’ll use regression discontinuity design (RDD) as a form of natural experiment that works as an alternative to A/B testing. RDD measures treatment effects at points of discontinuity to get an idea of the effectiveness of a program without needing to rigorously A/B test it. You’ll use this technique to assess the discounting strategy of an e-commerce company, in a way that will allow you to start applying causal inference to other practical problems.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Matheus Facure
Matheus Facure is an economist, data scientist and causal inference specialist at Nubank. He currently works with adding causal inference capabilities to machine learning models with application in the credit card business, and acts as a consultant for other business areas inside Nubank, such as personal loans and marketing.

prerequisites

This liveProject is for data scientists with knowledge of Python, machine learning, and statistics. To begin this liveProject you will need to be familiar with the following:


TOOLS
  • Basics of Python
  • Basics of pandas
  • Basics of Matplotlib
  • Basics of NumPy
TECHNIQUES
  • Basics of data science
  • Basics of causal inference

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