This project provides an analysis of an A/B test performed on a website redesign for a Datacamp Competition. Python pandas, scipy and statsmodels packages are used to perform a hypothesis test on conversion statistics
The analysis includes 2 main parts.
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Statistical analysis: The script performs several statistical tests to compare the performance of the old and new versions of the website.
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Effect size calculation: The script also calculates effect sizes for the statistical tests. This can be used to quantify the magnitude of the differences between the old and new versions of the website.
"redesign.csv": This file contains the dataset provided by Datacamp, it includes information about user conversion statistics before/after an new launch page implementation and a new image set.
"ap_test.ipynb": Jupyter notebook that contains the data analysis and A/B test steps.
This project is licensed under the MIT License. See the LICENSE file for more details.
Contributions are welcome! If you want to contribute to this project, please fork the repository and submit a pull request with your changes.