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The Baruch Faculty Research Seminar Series on Business Analytics



Little Data: How Traditional Statistical Ideas Remain Relevant in a Big-Data World

April 14, 12:45 - 2:00 pm

SCIS Conference room (11-217 NVC)


E0634F55-B3C6-4862-96CE-029C44F8F53EAndrew Gelman 
Professor, Department of Statistics 
Professor, Department of Political Science 
1016 Social Work Bldg (Amsterdam Ave. at 122 St.), 212-851-2142, dept. fax 851-2164 
Columbia University, New York, NY 10027



Description of the Talk:

“Big Data” is more than a slogan; it is our modern world in which we learn by combining information from diverse sources of varying quality.  But traditional statistical questions—how to generalize from sample to population, how to compare groups that differ, and whether a given data pattern can be explained by noise—continue to arise.  Often a big-data study will be summarized by a little p-value.  Recent developments in psychology and elsewhere make it clear that our usual statistical prescriptions, adapted as they were to a simpler world of agricultural experiments and random-sample surveys, fail badly and repeatedly in the modern world in which millions of research papers are published each year.  Can Bayesian inference help us out of this mess?  Maybe, but much research will be needed to get to that point.

About the Speaker
Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best articlepublished in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina).

Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.


To register, please complete the registration form:

For more information, please contact: Nanda Kumar (, SCIS, or Radhika Jain (, SCIS.  

This program is supported by the Office of the Provost’s Faculty Research Seminars

Members of the Faculty Research Seminar Series on Business Analytics

  • Radhika Jain, Nanda Kumar, Kannan Mohan, and Isak Taksa - CIS 
  • Kamiar Rahnama Rad/Junyi Zhang - Statistics 
  • Mahima Hada, David Luna, Karthik Sridhar, Cliff Wymbs - Marketing
  • David Anderson, Shan Li, Will Millhiser - Management