Project at the University of Pennsylvania, Fall 2022
This sample memo was practice for communicating heavy data-based reasoning in plain language for a non-technical audience. It required advocating for using algorithms to estimate recidivism of applicants to an ex-prisoner job program, a very sensitive topic that balances societal and individual impact.
The modeling and cost-benefit analysis is based on cleaned data from Public Policy Analytics textbook, Chapter 7 and similar job training programs.
- R Tidyverse Packages and Markdown for data wrangling, modeling, and cost benefit analysis
- Policy research
- Concise, non-technical communication of technical concepts and conclusions