2008/02/01 by David R. Brillinger · 1 citation
Arts and Humanities · Mathematics · #Philosophy and History of Science #stat.ME
paper · pdf · doi:10.1214/08-sts246rej
published as Statistical Science 2008, Vol. 23, No. 1, 76-77 · Published in at http://dx.doi.org/10.1214/08-STS246REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2008/02/01 · arxiv created 2008/08/05 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
I was so fortunate as to spend formative periods of my statistical career watching and working near two of the powerhouses of twentieth-century statistics—Jerzy Neyman (JN) and John Tukey. The first championed the responsibility the statistician has to set down a clear pertinent set of assumptions guiding her/his data analy-ses. The second emphasized the importance of looking for discoveries and surprises in data sets. The Neyman Lecture gave me an opportunity to show my admiration for Professor Neyman and his applied work. The examples from my own work are meant to parallel analyses from his work. In some cases the analyses were done some years ago. The paper may be considered a substantial update of Brillinger (1983). Both Grace Yang and Hans Künsch add meat to the paper and thereby increase our understanding of Jerzy Neyman and his contributions. I begin with Grace’s Discussion. Her comments “res-onate ” with me, to use her word. Indeed her Discus-sion, with its emphasis on Neyman’s teaching and re-search projects on sampling and cancer, creates here a collaborative paper concerning Neyman’s applied sta-tistics career. As well as lively anecdotes, Grace presents some Neyman quotes. One that she found that I like particu-larly is, I deeply regret the not infrequent emphatic declarations for or against pure theory and for or against work in applications. It is my strong belief that both are important and, certainly, both are interesting. The various quotes plus Grace’s own words bring out Neyman’s approach to science in general and statistics in particular. I refer you to the second paragraph in her section “Neyman as a teacher and his problem-driven approach. ” Grace further emphasizes today’s appear-ance of massive data sets and the steady appearance