Larry V. Hedges is one of eight Board of Trustees Professors at Northwestern University, the university’s most distinguished academic position. He holds appointments in the departments of Statistics, Psychology, in the School of Education and Social Policy, and in the Institute for Policy Research. Previously, he was the Stella M. Rowley Distinguished Service Professor at the University of Chicago.
Hedges’ research straddles many fields—in particular those of statistics, psychology, and educational policy. He is best known for his work on statistical methods for meta-analysis and its applications to evidence-based policy. He has also worked on the design of social experiments, the assessment of student achievement nationally and cross nationally, the role of uncertainty in basic models for cognition in psychology, and the demography of talent.
He was editor of the Journal of Research on Educational Effectiveness, the Journal of Educational and Behavioral Statistics, was Quantitative Methods Editor of Psychological Bulletin, and Associate Editor of the American Journal of Sociology. He has authored or co-authored numerous journal articles and eight books, including Statistical Methods for Meta-Analysis (with I. Olkin, Elsevier, 1985) and The Handbook of Research Synthesis and Meta-Analysis (with H. Cooper and J. Valentine, Russell Sage, 2009).
He is an elected member of the National Academy of Education and is a fellow of the American Academy of Arts and Sciences, the American Statistical Association, the American Psychological Association, and the American Educational Research Association. He is president of the Society for Research on Educational Effectiveness. He was nominated by President Obama to the Board of Directors of the National Board for Education Sciences and was confirmed by the U.S. Senate in this position in June 2012.
The award ceremony will take place on 10/24 (Thu) at 6:30 p.m. at the East Bank Club. You may sign up for the dinner here.
The abstract of his talk is below.
Big Data with Big Consequences, but Who Will Benefit?
It is an article of faith that big data will have profound consequences for science and for society. Many of the consequences are unlikely to be understood for some time. Of special interest to statisticians is what consequences big data may bring for our field. Many of the methods used in conjunction with big data efforts were invented or perfected by statisticians. Thus the advent of interest in big data could make statistics “the sexiest field around” as one commentator has suggested. However, it is easy to imagine that others fields could eclipse statistics as the principal source of inspiration and training for working with big data, to the detriment of both statistics and the sciences that hope to benefit from big data. An example of recent work on the problem of statistical disclosure control in big educational data illustrates some surprising benefits of statistical work in this context.