This textbook presents the essential tools and core concepts of data
science to public officials, policy analysts, and economists among
others in order to further their application in the public sector. An
expansion of the quantitative economics frameworks presented in policy
and business schools, this book emphasizes the process of asking
relevant questions to inform public policy. Its techniques and
approaches emphasize data-driven practices, beginning with the basic
programming paradigms that occupy the majority of an analyst's time and
advancing to the practical applications of statistical learning and
machine learning. The text considers two divergent, competing
perspectives to support its applications, incorporating techniques from
both causal inference and prediction. Additionally, the book includes
open-sourced data as well as live code, written in R and presented in
notebook form, which readers can use and modify to practice working with
data.