Andrew Gelman
Andrew Gelman 2012.jpg
Gelman in 2012
Born (1965-02-11) February 11, 1965 (age 57)
Alma materMassachusetts Institute of Technology
Harvard University
AwardsCOPSS Presidents' Award (2003)
Scientific career
InstitutionsColumbia University
Doctoral advisorDonald Rubin

Andrew Gelman (born February 11, 1965) is an American statistician, professor of statistics and political science at Columbia University. He earned a bachelor's degree in mathematics and in physics from MIT, where he was a National Merit Scholar, in 1986. He then earned a Ph.D. in statistics from Harvard University in 1990 under the supervision of Donald Rubin.[1][2]

He has received the Outstanding Statistical Application award from the American Statistical Association three times.[3] He is an elected fellow of the American Statistical Association[4] and the Institute of Mathematical Statistics.[5] He was elected fellow of the American Academy of Arts and Sciences (AAAS) in 2020.[6]

Personal life

Gelman is a participant in Study of Mathematically Precocious Youth.[7]

Gelman married Caroline Rosenthal in 2002[8] and has three children.[9]

The psychologist Susan Gelman is his older sister.[10] The cartoonist Woody Gelman was his uncle.[11]


Speaking at the University of Washington in 2017.
Speaking at the University of Washington in 2017.

Gelman is currently a professor of political science and statistics at Columbia University.[12] Gelman is a major contributor to statistical philosophy and methods especially in Bayesian statistics[13] and hierarchical models.[14]

He led the development of the statistical programming framework Stan.

Perspective on Statistical Inference and Hypothesis Testing

Gelman's approach to statistical inference places primary emphasis on the understanding of sources of variation and the estimation of meaningful quantities that represent answers to substantive questions in social and biological science.

He observes that his approach to hypothesis testing is "(nearly) the opposite of the conventional view"[15] 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 connects this to confirmationist and falsificationist paradigms of science.[16]

Gelman's critical approach to statistical inference is a major recurring theme of his works, his popular blog, and his many published works on statistical inference.[17]

Popular press

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",[18] blog published by The Washington Post. The blog is dedicated to providing informed commentary on politics and making political science more accessible.[19]

Gelman also keeps his own blog which deals with statistical practices in social science.[20] He frequently writes about Bayesian statistics, displaying data, and interesting trends in social science.[21][22][23] 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."[24]

Gelman is a prominent critic of poor methodological work and he identifies such work as contributing to the replication crisis.[24]



  1. ^ Andrew Gelman at the Mathematics Genealogy Project
  2. ^ Kesselman, Ellie (10 September 2014). "Statistics comes to Swarthmore College". Retrieved 19 November 2016. ...familiar name on that very short list of all Harvard Statistics PhD alumni: Columbia University political science and statistics professor Andrew Gelman in 1990
  3. ^ "Outstanding Statistical Application Award". American Statistical Association. Archived from the original on 8 April 2016.
  4. ^ ASA Fellows: Archived 2020-04-09 at the Wayback Machine
  5. ^ IMS Fellows: Archived 2014-03-02 at the Wayback Machine
  6. ^ "AAAS Fellows Elected" (PDF). Notices of the American Mathematical Society. 67.
  7. ^ "Life Paths and Accomplishments of Mathematically Precocious Males and Females Four Decades Later"
  8. ^ "WEDDINGS; Caroline Rosenthal, Andrew Gelman". The New York Times. 2002-05-12. ISSN 0362-4331. Archived from the original on 2017-12-13. Retrieved 2016-11-03.
  9. ^ "The way science works…or doesn't". Life After Baby. Archived from the original on 2017-12-14. Retrieved 2016-11-03.
  10. ^ Galef, Julia; Gelman, Susan (December 13, 2015). "Susan Gelman on 'How essentialism shapes our thinking'". Rationally Speaking: Official Podcast of New York City Skeptics. Episode RS 149. Archived from the original on June 25, 2018. Full transcript (PDF). Retrieved May 12, 2018.
  11. ^ Gelman, Andrew (14 July 2006). "Uncle Woody". Statistical Modeling, Causal Inference, and Social Science. Archived from the original on 25 December 2018. Retrieved 5 July 2018.
  12. ^ Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University:
  13. ^ Andrew Gelman, John B. Carlin, Hal S. Stern and Donald B. Rubin. "Bayesian Data Analysis" (2nd edition). Chapman & Hall/CRC, 2003. ISBN 978-1-58488-388-3
  14. ^ Gelman, Andrew (2006). "Multilevel (hierarchical) modeling: what it can and cannot do" (PDF). Technometrics. 48 (3): 432–435. doi:10.1198/004017005000000661. S2CID 7974250. Archived (PDF) from the original on 6 May 2006.
  15. ^ "What hypothesis testing is all about. (Hint: It's not what you think.) | Statistical Modeling, Causal Inference, and Social Science". Retrieved 2022-02-10.
  16. ^ "Confirmationist and falsificationist paradigms of science | Statistical Modeling, Causal Inference, and Social Science". Retrieved 2022-03-31.
  17. ^ Gelman, Andrew; Hill, Jennifer; Vehtari, Aki (2020-07-23). "Regression and Other Stories". Higher Education from Cambridge University Press. Retrieved 2022-02-10.
  18. ^ "Monkey Cage". The Washington Post. Retrieved 19 November 2016.
  19. ^ "Why this blog?" The Monkey Cage
  20. ^ Statistical Modeling, Causal Inference, and Social Science:
  21. ^ How Do I Make My Graphs?:
  22. ^ Exponential Increase In The Number of Stat Majors:
  23. ^ Everyone's trading bias for variance at some point, it's just done at different places in the analyses:
  24. ^ a b Dominus, Susan (2017-10-18). "When the Revolution Came for Amy Cuddy". The New York Times. ISSN 0362-4331. Retrieved 2017-10-19.