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What are the most important statisticians, and what is it that made them famous?
(Reply just one scientist per answer please.)

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    $\begingroup$ Converted to community wiki. $\endgroup$
    – user88
    Dec 4, 2010 at 0:14
  • $\begingroup$ what is community wiki? $\endgroup$ Dec 4, 2010 at 0:53
  • $\begingroup$ @Mariana: sharepointoverflow.com/questions/432/what-is-community-wiki $\endgroup$ Dec 4, 2010 at 4:32
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    $\begingroup$ @Mariana The idea is that pools and list-ofs are converted to a form in which they can be easily managed (due to lower rep req to edit) and voted up/down without hurting participants' reputation (votes on CW posts does not give/take reputation). $\endgroup$
    – user88
    Dec 4, 2010 at 16:01
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    $\begingroup$ If it weren't CW it would have to be closed as subjective and argumentative! $\endgroup$
    – whuber
    Dec 21, 2010 at 19:37

47 Answers 47

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Emanuel Parzen for kernel density estimation and reproducing kernel Hilbert space theory for stochastic processes.

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    $\begingroup$ I think Rosenblatt invented kde several years before Parzen. $\endgroup$ Aug 10, 2011 at 2:33
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It's very difficult to add to the constellation of stars that are already listed, but for interest purposes I will throw in the improbable polymath John Maynard Keynes who many would not realize published A Treatise on Probability (1921) that can be downloaded here; and whose work was quoted frequently by Harold Jeffreys (1939).

Keynes by all accounts helped to bring forward Bayesian statistics and in his treatise considered the most important principle to be the Principle of Indifference.

According to Wikipedia, The "Principle of insufficient reason" was renamed the "Principle of Indifference" by the economist John Maynard Keynes (1921), who was careful to note that it applies only when there is no knowledge indicating unequal probabilities.

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Robert Gentleman and Ross Ihaka for being the two initiators of and later main contributors of R, see https://cran.r-project.org/doc/html/interface98-paper/paper_1.html

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  • $\begingroup$ +1 R programming language has brought joy to Statistics in general. $\endgroup$ Jul 31, 2022 at 23:02
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William Cleveland, for either coining or popularising the term 'data science', but more importantly for contributions to data visualisation including the popular 'dot plot', and contributions to nonparametric regression such as loess smoothing.

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Brian Ripley for contributions to spatial statistics, neural network from statistician point of view, and a lot of other contributions, not the least of them being a main contributor to the success of R!

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Vladimir Vapnik:

For his fundamental contributions to our understanding of machine learning, which allows computers to classify new data based on statistical models derived from earlier examples, and for his invention of widely used machine learning techniques.

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Irving John Good for contributions, among others, to Bayesian Statistics. He learnt probability from Turing at Bletchley Park. Some of his ideas was mentioned at What is the role of the logarithm in Shannon's entropy? which has references.

He was also a consultant for Kubrick at the famous film 2001: A Space Odyssey.

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Teuvo Kohonen for invention of the Self-Organizing-Map (SOM).

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    $\begingroup$ and maybe also Bishop, Svensen and Williams for putting SOM on a clean probabilistic footing via the Generative Topographic Mapping. (And I didn't down vote anything either...) $\endgroup$ Dec 23, 2010 at 23:13
  • $\begingroup$ self-organizing precursors of Kohonen included Alan Turing (1952), Willshaw, Bunenman and Longuet-Higgens (1960s) and von der Malsburg (1973). (Didn't down vote anything either...) $\endgroup$ Mar 29, 2016 at 11:35
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I'd like to also add William Gemmell Cochran who is well known for establishing (or directing studies at) some of the preeminent statistics departments such as at Iowa State University, Harvard, Cambridge, that educated hundreds of future statisticians. His methods on Survey Sampling Techniques and Design and Analysis of Experiments are still widely used today.

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Bill James for his work in statistics that evaluate MLB player performance. His work spawned the term Sabermetics. He has created numerous statistics that can be found throughout the baseball world. His ideas stem from how to capture a player's overall impact on a game through run production (offense) and runs saved (defense). His work has led to less emphaisis on statistics that have low correlation to run production (batting average) and more on OPS (on-base + slugging). He works as an advisor to the Boston Red Sox and is credited to the World Series Championships in 2004 and 2007. His work has influenced the book and upcoming feature film Moneyball.

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    $\begingroup$ What about Nate Silver then? $\endgroup$ Oct 18, 2013 at 17:53
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If you judge based on the number of times their work is cited, E. L. Kaplan and Paul Meier since their 1958 paper "Nonparametric Estimation from Incomplete Observations" is widely regarded as the most cited paper in statistics.

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Joseph Hilbe (1944-), first president of the International Astrostatistics Association and author of over 10 books on statistical modeling, including popular texts on count models, logistic regression, generalized estimating equations (GEE), generalized linear models, and statistical methodology. Hilbe is an emeritus professor at the University of Hawaii and adjunct professor of statistics at Arizona State University.

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John Kingman for Coalescent theory and his work on completely random measures

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Harald Cramér was a swedish statistician, mathematician and actuary. John Kingman described him as "one of the giants of statistical theory".

Among his first works was application of probability in number theory. His 1946 book Mathematical Methods of Statistics was very influential, in showing a place for mathematical rigour in statistics. Most people will have heard about the Cramér-Rao inequality.

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Lotfi A. Zadeh, who not only coined the terms "fuzzy set" and "fuzzy logic", but invented many of the accompanying fuzzy statistics (like the sigma count, for instance).

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Jerome Harold Friedman for his contributions on CART (jointly with Leo Breiman in 1984), gradient boosting machines and partial dependence plots. Plus being co-author of the book (ESL)...

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Peter Bentler has made significant contributions to the implementation (e.g., his software EQS) and theory underlying structural equation modeling (SEM).

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