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🔥 A/B Testing

Data scientist | Anass MAJJI

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🧐 Description

In this project, we will take a deep dive into the main characteristics of the A/B Testing and it applications. We are going to hightlight the following steps :

* 1 - The meaning of A/B Test and usecases.
* 2 - Make hypothesis (H0) and (H1).
* 3 - Define a metric. 
* 4 - Compute a minimum sample size required to have statistically significant results.
* 5 - Choose Two-Tailed or One-Tailed test depending on situations. 
* 6 - Reject or keep the null hypothesis (H0). 

🚀 Repository Structure

The repository contains the following files & directories:

• README.md : The top level README for reviewers of this project.

• Images: It contains the images used on the notebook/ Readme file.

• A_B_Testing.ipynb : a notebook detailling the A/B test steps.

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📪 Contact

For any information, feedback or questions, please contact me