This project was completed as part of Udacity's Data Analyst Nanodegree.
A/B tests are very commonly performed by data analysts and data scientists. For this project, I work to understand the results of an A/B test run by an e-commerce website, with data provided by Udacity. The goal is to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.
- Jupyter Notebook
- Pandas
- Numpy
- Matplotlib
- Statsmodels
To get the Jupyter Notebook running, execute the following in the command line and select ab-test.ipynb from the Jupyter Notebook dashboard. The conda environment setup is optional; I have provided the base environment in base.yaml.
$ git clone https://github.com/evanchen13/ab-test.git
$ cd ab-test
$ conda env create -f base.yaml
$ jupyter notebook
The contents of this repository are covered under the GNU General Public License v3.0.