New IMS President Susan Murphy was interviewed at the International Statistical Institute’s 62nd World Statistics Congress, which was held in Kuala Lumpur in August. You can watch her talking with Anne Edwards in the WebTV section of the ISI2019 website, at https://www.isi2019.org/isi-wsc-2019-webtv/ Also interviewed were the Presidents — all women — of the other four international statistical societies that created the International Prize in Statistics: Karen Kafadar of the American Statistical Association (ASA), Louise Ryan of the International Biometric Society (IBS), Helen MacGillivray of the International Statistical Institute (ISI), and Deborah Ashby of the Royal Statistical Society (RSS). Several other leading statisticians were also interviewed; see the same webpage for the videos.

The second International Prize in Statistics was presented to the winner, Bradley Efron

At the congress, the second International Prize in Statistics was presented to the winner, Bradley Efron, professor of statistics and biomedical data science at Stanford University. He received the prize in recognition of the “bootstrap,” a method he developed in 1977 for assessing the uncertainty of scientific results that has had extraordinary impact across many scientific fields. Brad Efron participated in the award ceremony through a video message; ISI President Helen MacGillivray received the prize certificate on his behalf. Brad also gave his prize-winner’s lecture via a video linkup.

Bradley Efron gave his prize lecture via video link


The lecture, “Prediction, estimation, and attribution,” examined the changing scientific needs and computational limitations that have fashioned classical statistical methodology. According to his abstract: “Large-scale prediction algorithms—neural nets, deep learning, boosting, support vector machines, random forests—have achieved star status in the popular press. They are recognizable as heirs to the regression tradition, but ones carried out at enormous scale and on titanic data sets. How do these algorithms compare with standard regression techniques such as Ordinary Least Squares or logistic regression? Several key discrepancies will be examined, centering on the difference between prediction and estimation or attribution (significance testing).”

The other activities of the World Congress are detailed in the report by the organizers, at https://www.isi-web.org/images/WSC/2019/Report-62nd-ISI-WSC-2019.pdf