Taeil Goh | Greg Tozzi | Max Ziff | December, 2020
This is our final project for the experiments and causal inference course of the UC Berkeley School of Information's Master of Information and Data Science program. We conducted A/B testing of email subject and from lines to support a non-profit's year end fundraising surge.
Skills demonstrated: Causal inference | Regression | Literate programming
Languages and frameworks: R | data.table | knitr
├── README.md <- The top-level README for developers using this project.
├── data
│ └── raw <- The original, immutable data dump.
├── notebooks <- intermediate Rmd files
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Graphics and figures to be used in reporting
└── src <- Source code for use in this project.
Project based on the cookiecutter data science project template. #cookiecutterdatascience