This lecture took place on Friday, October 4th at 11:00 a.m. in 214 Duxbury Hall. Recording of the talk
FSU Announces Robert E. Kass as 2024 Myles Hollander Distinguished Lecturer
The Department of Statistics at Florida State University is pleased to announce that Robert E. Kass, the Maurice Falk University Professor of Statistics and Computational Neuroscience in the Department of Statistics and Data Science, the Machine Learning Department and the Neuroscience Institute at Carnegie Mellon University, is the 2024 Myles Hollander Distinguished Lecturer.
Kass will present “Reasoning from Data in Science,” at 11 a.m., Friday, Oct. 4, 2024, on FSU’s Tallahassee campus. The live talk will also be accessible via Zoom.
Lecture Abstract
In statistical research and teaching, we rightly focus on technical methods but, in my view, especially in teaching, the underlying attitudes and principles are often given too little attention. I will use examples drawn from neuroscience to illustrate three general themes that help explain many great advances in reasoning from data: rigor, faith and pragmatism.
This high-level, conceptual lecture will avoid details and anyone who may want more, or may want to read ahead, should visit stat.cmu.edu/~kass/ to review the relevant publications. Parts of my perspective were articulated in my 2011 article, “Statistical Inference: The Big Picture” and my 2021 commentary, “The Two Cultures: Statistics and Machine Learning in Science.” The data I will discuss are neural spike trains and local field potentials recorded from electrodes within the brain. The context may be found in a 2018 article I wrote with 24 others for the Annual Reviews. The methods are summarized (without math, aiming at experimentalists) in a 2023 review I wrote with four of my graduate trainees for the Journal of Neurophysiology.
About the Speaker
Robert E. Kass received a B.A. in mathematics from Antioch College (1975), a Ph.D. in statistics from the University of Chicago (1980) and was a postdoctoral fellow at Princeton University before joining Carnegie Mellon University in 1981. His early work formed the basis for his co-authored book “Geometrical Foundations of Asymptotic Inference,” and his subsequent research has sought to understand how reasoning from data produces reliable scientific knowledge. For Bayesian inference, Kass and colleagues provided comprehensive reassessment of the evaluation of evidence concerning hypotheses and determination of prior probabilities. Kass is a leader in the application of statistics to neuroscience, where he has focused on tractable data-analytic statistical models for spike trains, i.e., data representing the primary mode of communication among neurons, and co-authored the book “Analysis of Neural Data.”
Kass served as chair of the Statistics Section of the American Association for the Advancement of Science, founding editor-in-chief of the journal Bayesian Analysis, and executive editor of the international review journal Statistical Science. He received the Outstanding Statistical Application Award from the American Statistical Association and the Distinguished Achievement Award and Lectureship from the Committee of Presidents of Statistical Societies. Kass is an elected Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science, and an elected member of the National Academy of Sciences.
The Myles Hollander Distinguished Lectureship is sponsored by:
