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🌟 Project 4: A/B Testing & Statistics on Olist Data

🧩 Context and Objectives

This one-day project aimed to explore a subset of the public Olist dataset (Brazil) in order to formulate business hypotheses, extract descriptive insights, and test hypotheses using statistical and A/B testing methods. The approach relied on analysis in Python (pandas, numpy, plotly express) and included an oral presentation of the results.

πŸ“Š Data Used

πŸ” Methodology

πŸ“ˆ Results

πŸ“Œ Tools

Python (pandas, numpy, plotly, scipy.stats), Jupyter

πŸ—£οΈ Presentation

Synthetic slides with visualizations + explanation of tests

View the notebook on Google Colab