Most famous statisticians What are the most important statisticians, and what is it that made them famous?
(Reply just one scientist per answer please.)
 A: Ronald Fisher for his fundamental contributions to the way we analyze data, whether it be the analysis of variance framework, maximum likelihood, permutation tests, or any number of other ground-breaking discoveries. 
A: Samuel S. Wilks was a leader in the development of mathematical statistics. He developed the theorem on the distribution of the likelihood ratio, a fundamental result that is used in a wide variety of situations.  
He also helped found the Princeton statistics department, where he was Fred Mosteller's advisor, among others, and has a prestigious ASA award named after him.
A: Abraham Wald (1902-1950) for introducing the concept of Wald-tests and for his fundamental work on statistical decision theory.
A: John Nelder, for providing us the now omnipresent generalized linear model framework. By his approach of unifying various standard statistical models and its estimation method, the iteratively reweighted least squares method for ML, he gave us tools that we are using now in almost all applied and theoretical concepts that are related to exponential family models. Not to mention his contributions to optimization as the superb Nelder-Mead-Algorithm.
A: David Donoho development of multiscale ideas in statistics, and a lot of theoretically justified while practically very efficient ideas in very high dimensional statistics, CHA: computational harmonic analysis,... 
A: Lucien Le Cam for his contribution to mathematical statistics. (maybe Local asymptotic normality and contiguity made him famous)
A: Leland Wilkinson for his contribution to statistical graphics.
A: Adolphe Quetelet for his work on the "average man", and for pioneering the use of statistics in the social sciences.  Before him, statistics were largely confined to the physical sciences (astronomy, in particular).
A: Emanuel Parzen for kernel density estimation and reproducing kernel Hilbert space theory for stochastic processes.
A: 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.
A: 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
A: 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.
A: John Tukey for Fast Fourier Transforms, exploratory data analysis (EDA), box plots, projection pursuit, jackknife (along with Quenouille). Coined the words "software" and "bit".
A: Reverend Thomas Bayes for discovering Bayes' theorem
A: Karl Pearson for his work on mathematical statistics.  Pearson correlation, Chi-square test, and principal components analysis are just a few of the incredibly important ideas that stem from his works.
A: Carl Gauss for least squares estimation.
A: 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!
A: William Sealy Gosset for Student's t-distribution and the statistically-driven improvement of beer.
A: Bradley Efron for the Bootstrap - one of the most useful techniques in computational statistics.
A: Andrey Nikolayevich Kolmogorov, for putting probability theory on a rigorous mathematical footing. While he was a mathematician, not a statistician, undoubtedly his work is important in many branches of statistics.
A: 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.
A: 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.
A: Pierre-Simon Laplace for work on fundamentals of (Bayesian) probability.
A: Francis Galton for discovering statistical correlation and promoting regression. 
A: George Box for his work on time series, designed experiments and elucidating the iterative nature of scientific discovery (proposing and testing models).
A: Andrey Markov for stochastic processes and markov chains. 
A: Teuvo Kohonen for invention of the Self-Organizing-Map (SOM).
A: 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.
A: Jerzy Neyman and Egon Pearson for work on experimental design, hypothesis testing, confidence intervals, and the Neyman-Pearson lemma.
A: How has Sir David Roxbee Cox not been mentioned yet?   
Some feats:  Cox proportional hazards models, experimental design, he did a lot of work on stochastic processes and binary data.  He also advised many students who went on to do great work (Hinkley, McCullagh, Little, Atkinson, etc.)
And the man was knighted!
A: Leo Breiman for CART, bagging, and random forests.
A: Harold Jeffreys for revival of Bayesian interpretation of probability.
A: Edwin Thompson Jaynes for work on objective Bayesian methods, particularly MaxEnt and transformation groups.
A: Florence Nightingale for being "a true pioneer in the graphical representation of statistics" and developing the polar area diagram. Yes, that Florence Nightingale!
A: C.R. Rao for the Rao–Blackwell theorem and the Cramer-Rao bound.
A: Blaise Pascal and Pierre de Fermat for creating the theory of probability and inventing the idea of expected value (1654) in order to solve a problem grounded in statistical observations (from gambling).
A: 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.
A: 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.
A: Roderick Little and Donald Rubin for the contributions in Missing Data Analysis.
A: W. Edwards Deming for promoting statistical process control
A: George Dantzig for the Simplex Method, and for being the student who mistook two open statistics problems that Neyman had written on the board for homework problems, and in his "ignorance" solving them. I'd vote for him just for the story.
A: 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.
A: John Kingman for Coalescent theory and his work on completely random measures
A: 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.
A: 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).
A: 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)...
A: Peter Bentler has made significant contributions to the implementation (e.g., his software EQS) and theory underlying structural equation modeling (SEM).
