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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Reverend Thomas Bayes for discovering Bayes' theorem |
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Carl Gauss for least squares estimation. |
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John Tukey for Fast Fourier Transforms, exploratory data analysis (EDA), box plots, projection pursuit, jackknife (along with Quenouille). Coined the words "software" and "bit". |
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Florence Nightingale for being "a true pioneer in the graphical representation of statistics" and developing the polar area diagram. Yes, that Florence Nightingale! |
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George Box for his work on time series, designed experiments and elucidating the iterative nature of scientific discovery (proposing and testing models). |
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Roderick Little and Donald Rubin for the contributions in Missing Data Analysis. |
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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. |
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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! |
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Leo Breiman for CART, bagging, and random forests. |
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Francis Galton for discovering statistical correlation and promoting regression. |
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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. |
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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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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). |
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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,... |
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W. Edwards Deming for promoting statistical process control |
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Leland Wilkinson for his contribution to statistical graphics. |
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Jerzy Neyman and Egon Pearson for work on experimental design, hypothesis testing, confidence intervals, and the Neyman-Pearson lemma. |
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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). |
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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. |
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Lucien Le Cam for his contribution to mathematical statistics. (maybe Local asymptotic normality and contiguity made him famous) |
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Emanuel Parzen for kernel density estimation |
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Teuvo Kohonen for invention of the Self-Organizing-Map (SOM). |
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William Sealy Gosset for Student's t-distribution and the statistically-driven improvement of beer. |
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Bradley Efron for the Bootstrap - one of the most useful techniques in computational statistics. |
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Harold Jeffreys for revival of Bayesian interpretation of probability. |
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Edwin Thompson Jaynes for work on objective Bayesian methods, particularly MaxEnt and transformation groups. |
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Andrey Markov for stochastic processes and markov chains. |
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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. |
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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. |
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