It is a daunting task to discuss this topic in a session with presentations by two giants of our field, David Cox and Peter Huber, and a discussion by Steven Stigler, whose knowledge of the history of statistics dwarfs anything that I know about it. Consequently, my presentation will be somewhat idiosyncratic and focus more on how I see statistics evolving from what it was in my early years in it, to what it is for me now, followed by some highly speculative extrapolations, which can be summarized by some key words: Bayesian, causality, design, and simulation.

Keywords: Bayesian; Causality; Design; Simulation

Biography: Donald B. Rubin, John L. Loeb Professor of Statistics, Department of Statistics, Har-vard University, has authored or coauthored over 350 publications, and has made important contributions to statistical theory and methodology, particularly in causal inference, sample survey design, treatment of missing data, and Bayesian methods. He has been awarded the Wilks Medal (1995), Parzen Prize (1996), Fisher Lectureship (2004), Mitchell Prize (2001, 2009), Snedecor Award (2007), and Wiley Lifetime Achievement Award (2004). He was elected Fellow of the American Academy of Arts and Sciences (1993), Honorary Member of the European Association of Methodology (2008), Fellow of the British Academy (2009) and of the U.S. National Academy of Sciences (2010); he is also a Fellow of the Woodrow Wilson Society (1965), American Statistical Association (1977), Institute of Mathematical Statistics (1977), John Simon Guggenheim Foundation (1984), American Association for the Advancement of Science (1984) and Alexander von Humboldt Foundation (2009).