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Abstract:
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In this age of massive data, machine learning algorithms, and multiple on-line sources of tools for data analysis, what does statistics have to offer? I will recall several situations where statistics made a real difference. Sometimes the difference lay in the insightful analysis and inference enabled by ground-breaking methods in our field (hypothesis testing, likelihood ratios, Bayesian models, jackknife, bootstrap). But often the impacts arose from thoughtful analyses before data were collected (understanding the problem, designing the experiment and data collections, conducting the pilot surveys), and the questions that the statisticians raised through sensible explorations following formal statistical procedures (e.g., need for replication). I will present a few examples -- some known and familiar to all, now so ingrained in our practice that the role of statistics has been forgotten (e.g., randomization in clinical trials), and others which may be less familiar but nonetheless benefited critically from statisticians' input -- thereby reminding us that our field today remains not only relevant but critical to science and society.
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