People News for April
Richard Allen and Donald Bay
The U.S. Department of Agriculture’s National Agricultural Statistics Service (NASS) recently inducted into its hall of fame Richard D. Allen and Donald M. Bay, two retired agency leaders whose impact continues to resonate today.
The NASS Hall of Fame honors individuals whose work at the agency has had a lasting impact on agricultural statistics and the service NASS provides. Those inducted exemplify integrity, honesty, and commitment to public service.
“These accomplishments are built on a solid foundation formed by earlier NASS employees. We are reminded frequently of their contributions and are honored to have the opportunity to recognize some of them via the NASS Hall of Fame,” said NASS Administrator Hubert Hamer.
Allen was honored for leading with integrity and an unwavering desire to improve the quality and timeliness of agricultural statistics. As NASS historian and a compassionate mentor, his legacy includes the countless statisticians he helped develop into exceptional stewards of agricultural statistics.
Bay was honored for producing significant and lasting changes to NASS’ agricultural statistics program and organizational culture, including the transfer of the Census of Agriculture program from the U.S. Census Bureau to NASS. During a time of technological change, he skillfully maintained morale and implemented many efficiency measures.
Learn more about the NASS Hall of Fame, including how to submit a nomination, at the NASS website.
The Department of Planning, Development, and Research (DPDR) of the Ministry of Education in Brunei Darussalam organized a workshop on evidence-based decision making and meta-analysis with applications January 23–25, 2017, at the Rizqun International Hotel in Bandar Sri Begawan, Brunei.
Shahjahan Khan, professor of statistics at the University of Southern Queensland, presented the workshop.
The workshop emphasized the importance of being evidence-informed for the decision makers, especially the essence of the levels and quality of evidence including the design of studies. The systematic reviews, as opposed to narrative reviews, must avoid every kind of bias to make the systematic reviews and meta-analyses objective and reproducible.