Rejoinder: The 2005 Neyman Lecture: Dynamic Indeterminism in Science

Abstract

I was so fortunate as to spend formative periods ofmy statistical career watching and working near twoof the powerhouses of twentieth-century statistics—JerzyNeyman (JN) and John Tukey. The firstcham-pioned the responsibility the statistician has to setdown a clear pertinent set of assumptions guidingher/his data analyses. The second emphasized theimportance of looking for discoveries and surprisesin data sets.The Neyman Lecture gave me an opportunity toshow my admiration for Professor Neyman and hisapplied work. The examples from my own work aremeant to parallel analyses from his work. In somecases the analyses were done some years ago. Thepaper may be considered a substantial update ofBrillinger (1983). Both Grace Yang andHansKu¨nschadd meat to the paper and thereby increase our un-derstanding of Jerzy Neyman and his contributions.I begin with Grace’s Discussion. Her comments“resonate” with me, to use her word. Indeed herDiscussion, with its emphasis on Neyman’s teachingand research projects on sampling and cancer, cre-ates here a collaborative paperconcerning Neyman’sapplied statistics career.As well as lively anecdotes, Grace presents someNeyman quotes. One that she found that I like par-ticularly is,Ideeplyregret the notinfrequentemphaticdeclarations fororagainst puretheoryandfor or against work in applications. It ismy strong belief that both are importantand, certainly, both are interesting.