March 20, 2019

Castro Welcomes $50,000 NSF Grant to UTSA for Research on Data Analysis Training

SAN ANTONIO, TEXAS—Congressman Joaquin Castro (TX-20), Chairman of the Congressional Hispanic Caucus, Vice Chairman of the House Foreign Affairs Committee, and a member of the House Intelligence and Education and Labor Committee, today announced that the National Science Foundation (NSF) will award $50,000 to the University of Texas at San Antonio (UTSA) for a project designed to assist data analysts to better understand statistical tests, as well as guidance on how to report results.

“San Antonio is home to a vibrant and diverse workforce comprised of defense, cyber, and STEM personnel,” said Rep. Castro. “I am pleased to learn of the National Science Foundation’s intent to award the University of Texas at San Antonio $50,000 for research on data analysis training and application practices that can be useful across industries. As our community grows, it is vital that our workforce remains up-to-date with the most current tools and practices to meet present and future challenges. I welcome The University of Texas at San Antonio’s award, and look forward to the results of their research.”

Background: The National Science Foundation (NSF) has announced its intent to award $50,000 to the University of Texas at San Antonio (UTSA) for a project led by Dr. H. LeBlanc titled, “Interactive Statistical Decision Trees for Application in Real-world Contexts.” This funding is provided through the NSF I-Corps program, which seeks to extend the impact of basic research by funding projects that transfer innovative ideas from the academic setting towards commercialization and wider use. Dr. LeBlanc’s project aims to provide tools which can be used in medical or other industry settings to reduce training time for new data analysts. Using a series of decision steps and video demonstrations, the project is designed to assist data analysts in understanding the most appropriate statistical tests to apply in a particular situation, as well as guidance on how to report results.

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