Building Shiny Dashboards

Learn how to build a shiny dashboard in R to help users analyze, visualize, and understand their data.

26 min read Ben Hayes

Shiny dashboards provide a simple and fast way to analyze and visualize data. Whether performing exploratory data analysis or building a robust tool for your client's executives, Shiny dashboards aid the data science process. Continue reading to walk through an example of constructing an R Shiny Dashboard.

ACLU Data Science Internship

Data science for good: my internship with the ACLU in NYC

7 min read Ben Hayes

Data science can change how any organization operates not just Facebook or Amazon, but even the American Civil Liberties Union - an organization 10 times older than Facebook. Continue reading to learn about my experience interning with the ACLU's data science team in New York.

Predicting Criminal Recidivism with R

Can data science indicate what factors affect the rate of criminal or violent recidivism? (Hint: Yes)

45 min read Ben Hayes

Around the United States, municipalities have turned to risk assessment instruments (RAIs) to help judges determine which individuals to release on bail and which ones to keep in custody. The risk assessment process varies based on the specific instrument used but many rely on criminal recidivism data sets. These data sets typically contain various demographic indicators (age, race, gender, etc.) and also criminal history (charges, juvenile record, etc.).

Broward County, Florida, has turned to the use of one of the most popular RAIs today: COMPAS or the Correctional Offender Management Profiling for Alternative Sanctions tool. COMPAS assesses individuals based on criminal history and social profiling to categorize an individual as low, medium, or high risk. This tool, however, was not developed using the Broward County data set which may lead to poor performing predictions for individuals from Broward County, Florida. In this post we construct an RAI, compare to COMPAS and discuss findings.