This column is written for those interested in learning about the world of Data for Good, where statistical analysis is dedicated to good causes that benefit our lives, our communities, and our world. If you would like to know more or have ideas for articles, contact David Corliss.

With a PhD in statistical astrophysics, David Corliss leads a data science team at Fiat Chrysler. He serves on the steering committee for the Conference on Statistical Practice and is the founder of Peace-Work, a volunteer cooperative of statisticians and data scientists providing analytic support for charitable groups and applying statistical methods in issue-driven advocacy.

The American Statistical Association has awarded the 2019 Karl E. Peace Award for Outstanding Statistical Contributions for the Betterment of Society to statistician, author, and professor Joseph L. Gastwirth of The George Washington University (GW).

Established in memory of biostatistician and industry leader Karl E. Peace, the award is given each year to a person making “substantial contributions to the statistical profession, contributions that have led in direct ways to improving the human condition. Recipients will have demonstrated through their accomplishments their commitment to service for the greater good.”

Gastwirth’s work lies at the intersection of statistical analysis and the law. His career in statistics has focused on making an impact on peoples’ lives through the law and the many ways it affects society. In giving the award, the committee noted Gastwirth’s “distinguished career as a leading authority in the area of legal statistics, who has developed novel methodological and theoretical statistical approaches to address economic and health inequalities, to combat discrimination, and to advance civil rights and social justice.”

As an author, Gastwirth’s books have provided much-needed instruction for legal professionals on essential statistical concepts. He has also developed tools for statisticians working in the legal arena, including co-authoring the R package lawstat. This package performs several statistical tests and creates plots, providing real-world examples drawn from law, economics, policy, and biostatistics. Additionally, he has developed mathematical methods to capture and assess difficult-to-quantify concepts such as fairness in financial dealings.

Gastwirth’s early work focused on robust and nonparametric statistical methods. A long-time professor at GW, he became involved in the study of economic inequality—an area in which both robust and nonparametric methods are important. Statistical challenges in economic distributions and equality, in turn, led to statistics for law and policy. This resulted in teaching and writing for attorneys and law students, consulting on legal cases, and working on government policy. Gastwirth served as a visiting adviser to the Office of Management and Budget Office of Statistical Policy and a consultant for the Bureau of Labor Statistics on employment inequality. This work on the legal side of Data for Good led to consulting engagements and subsequent papers on statistical methods for law, including pyramid schemes and securities.

This lifetime of achievement in research and writing has had a wide-ranging effect on many areas. Beyond its impact in the courtroom, Gastwirth’s work has been important to the development of data-driven policy on economic inequality, discrimination, and human rights. Steve Pierson, the ASA’s Director of Science Policy, said, “I’m pleased that Joseph Gastwirth is the recipient of the Peace Award. Gastwirth’s contributions to the betterment of society have been broad and immense. In my science policy work for the ASA, Gastwirth and his work frequently come up as examples of the impact of statistics and statisticians on policy issues.”

To help people and establish justice, statistical human rights advocacy comes back to policy, practice, and law. This makes Gastwirth’s work valuable in turning statistical studies into effective action. Examples described in the lawstat package include gerrymandering, where the effective power of a person’s vote varies by voting district, and inequities in per-pupil student funding. While many might think of a Gini Index as a measure of economic disparity, it has no inherent economic tie and can be applied to variance in a variety of contexts. Lawstat can calculate the Gini Index as a measure of unequal distribution and provide plots and visualizations to help explain statistical results of Data for Good projects to the nonstatistical audiences needed to deliver effective action on the problems we seek to address.

In an era when statistical science is politicized and weaponized, Gastwirth focuses on using statistics to make a difference and better society. Working at the intersection of science and policy, his sound and reliable science for the greater good can both inspire and guide our work.