Collaborations between academia and industry in nutrition and health data science are shaped by a fundamental tension—academia seeks to generate generalizable knowledge, while industry is driven to produce timely, actionable, and consumer-relevant solutions. Rather than being a flaw, this difference is a defining feature.
A Statistician's View
As AI Does More Analytics, What Should Statisticians Do More Of?
AI can generate code, fit competing models, produce visualizations, and summarize results at a speed that would have been difficult to imagine not long ago. For statisticians, this raises an uncomfortable but useful question: As AI does more analytics, what should statisticians do more of?
From Model Accuracy to Data Reliability: A Practical Framework for ML Teams
Praveen Gupta Sanka discusses the Data Reliability Score, a framework developed with Vidya Sagar Minukuri. She says, “The idea is simple: As machine learning teams use quantitative metrics to decide whether a model is ready for deployment, they should also use quantitative metrics to decide whether the data is reliable enough to support that decision.”
A Statistician Is Not a Wrench! (An Allegory)
Nancy Geller, former ASA president, uses an allegory to tackle a frustration many statisticians know all too well: being called in after the data is collected.
From Participation to Impact: Advancing Statistical Capacity in Africa
Since its launch in 2014, the African International Conference on Statistics has grown into a continent-wide conference.
The Empty Seat: A Commentary on the Absence of Black African Statisticians at the African International Conferences on Statistics (2014–2025)
Saralees Nadarajah and Samuel Manda examine a troubling pattern at the African International Conferences on Statistics from 2014 to 2025.
Preparing a Confident Workforce: Starting Courses with a Meet-and-Greet
Jaya M. Satagopan, professor of biostatistics at the Rutgers School of Public Health, shares a simple intentional strategy to ensure students are emotionally ready to engage in her biostatistics course.
A Case Study in Publication Practices: Full House Modeling
Daniel J. Eck responds to David Banks’ earlier A Statistician’s View piece.
A Call for Thought
In this month’s Statistician’s View, David Banks of Duke University challenges the statistical community to take a hard look at our publication practices.
Statistician’s View: The Power of Collaboration in Statistics
I think Nick Beyler’s best sentence comes at the very end of his February 2025 STATtr@k column, says Barry Nussbaum. “Want to collaborate on something?” That’s the key to all our statistical work. To have impact, we use our talents as part of a team.