Andrew Gelman | |
|---|---|
Gelman in 2012 | |
| Born | February 11, 1965 |
| Nationality | American |
| Citizenship | American |
| Alma mater | Massachusetts Institute of Technology (SB) Harvard University (MA, PhD) |
| Children | 3 |
| Awards | COPSS Presidents' Award (2003) |
| Scientific career | |
| Fields | Statistics |
| Institutions | Columbia University |
| Thesis | Topics in Image Reconstruction from Emission Tomography (1990) |
| Doctoral advisor | Donald Rubin |
| Website | stat.columbia.edu/~gelman/ |
Andrew Eric Gelman[1] (born February 11, 1965) is an American statistician, professor of statistics and political science at Columbia University.
Gelman received bachelor of science degrees in mathematics and in physics from MIT, where he was a National Merit Scholar, in 1986. He then received a master of science in 1987 and a doctor of philosophy in 1990, both in statistics from Harvard University, under the supervision of Donald Rubin.[2][3][4]
He has received the Outstanding Statistical Application award from the American Statistical Association three times.[5] He is an elected fellow of the American Statistical Association[6] and the Institute of Mathematical Statistics.[7] He was elected fellow of the American Academy of Arts and Sciences (AAAS) in 2020.[8]
Gelman is a participant in Study of Mathematically Precocious Youth.[9]
Gelman married Caroline Rosenthal in 2002[10] and has three children.[11]
The psychologist Susan Gelman is his older sister.[12] The cartoonist Woody Gelman was his uncle.[13]
Gelman is currently a professor of political science and statistics at Columbia University.[14] Gelman is a major contributor to statistical philosophy and methods especially in Bayesian statistics[15] and hierarchical models.[16]
He led the development of the statistical programming framework Stan.
Gelman's approach to statistical inference emphasizes studying variation and the associations between data, rather than searching for statistical significance.[17]
Gelman says his approach to hypothesis testing is "(nearly) the opposite of the conventional view"[18] of what is normally done for statistical inference. While the standard approach may be seen as having the goal of rejecting a null hypothesis, Gelman argues that you can't learn much from a rejection. On the other hand, a non-rejection tells you something: "[it] tells you that your study is noisy, that you don't have enough information in your study to identify what you care about—even if the study is done perfectly, even if measurements are unbiased and your sample is representative of your population, etc. That can be some useful knowledge, it means you're off the hook trying to explain some pattern that might just be noise." Gelman has written a blog post on his work within the context of larger confirmationist and falsificationist paradigms of science.[19]
Gelman's unique approach to statistical inference is a major recurring theme of his works, his popular blog, and his many published works.[20]
Gelman is notable for his efforts to make political science and statistics more accessible to journalists and to the public. He was one of the primary authors of "The Monkey Cage",[21] blog published by The Washington Post. The blog is dedicated to providing informed commentary on politics and making political science more accessible.[22]
Gelman also keeps his own blog which deals with statistical practices in social science.[23] He frequently writes about Bayesian statistics, displaying data, and interesting trends in social science.[24][25][26] According to The New York Times, on the blog "he posts his thoughts on best statistical practices in the sciences, with a frequent emphasis on what he sees as the absurd and unscientific... He is respected enough that his posts are well read; he is cutting enough that many of his critiques are enjoyed with a strong sense of schadenfreude."[27]
Gelman is a prominent critic of poor methodological work and he identifies such work as contributing to the replication crisis.[27]
