A key measure of the maturity and quality of a scientific community is how it judges and values accomplishments and (or versus) scholarship. To address this question, I will describe the motivation or drive for accomplishments and/or scholarship at three levels: inspiration, aspiration, ambition. They represent different (but not necessarily exclusive) mindsets or modi operandi. I will use several prominent examples in statistics history to explain or illustrate the acts of inspiration, aspiration, and ambition. They include: Pearson’s arguments with Fisher and with Yule, some breakthrough work of Fisher, Neyman, Tukey, Box, Efron, etc. Then I will share some thoughts on what are good or bad mathematical statistics work. Throughout this talk, I will use the “lens” of inspiration, aspiration, and ambition in making my examinations, remarks and suggestions.
C. F. Jeff Wu is Professor and Coca Cola Chair in Engineering Statistics at the School of Industrial and Systems Engineering, Georgia Institute of Technology. He was the first academic statistician elected to the National Academy of Engineering (2004); also a Member (Academician) of Academia Sinica (2000). A Fellow of American Society for Quality, Institute of Mathematical Statistics, of INFORMS, and American Statistical Association. He received the COPSS (Committee of Presidents of Statistical Societies) Presidents’ Award in 1987, the COPSS Fisher Lecture Award in 2011, the Deming Lecture Award in 2012, the inaugural Akaike Memorial Lecture Award in 2016, the George Box Medal from Enbis in 2017, and numerous other awards and honors. He has published more than 170 research articles and supervised 45 Ph.D.'s. He has published two books "Experiments: Planning, Analysis, and Parameter Design Optimization" (with Hamada) and “A Modern Theory of Factorial Designs” (with Mukerjee).
