### Anirban DasGupta writes his last column, for now (he will be the new Bulletin editor from the next issue):

On July 18, 2013, I wrote an email to Steve Stigler, which said: “Dear Steve, has any well-known person made a list of what she or he considers to be the most major inventions/discoveries in statistics? I ask because I prefer to use another person’s list than write one myself.” On July 22, Steve thus replied: “Anirban, some time ago there was a list of 10 discoveries in the sciences and the chi-sq was one. I am working on a book on the five most consequential ideas in statistics, but it is quite different in scope and ﬂavor. So go ahead and make a list—my guess is that different people’s lists will show little overlap.”

So, blame it on Steve: here, in my last column for the Bulletin, I enter into the absurdly perilous territory of making a personal list of 215 inﬂuential and original developments in statistics, primarily to provide a sense of our lavish and multifarious heritage to a fresh PhD in statistics. I choose items that have inﬂuenced the research or practice or education or thinking of many people across the world; the criterion was not deep theorems *per se*, rather innovations and publications with a universal and scopic impact. The choices are of course personal, but not prejudicial; no one should take them too literally. I had it looked over by 13 very senior world statisticians. There is, predictably, an overlap of this expanded list with the Springer *Breakthroughs in Statistics* volumes. I list the items followed by what I know to be the ﬁrst serious suggestion or origin of the particular item; this is of course very difficult and some errors are likely! A more elaborate version with the publications corresponding to these 215 entries is available at www.stat.purdue.edu/~dasgupta.

## 215 Developments in Statistics:

Likelihood 1657, WLLN 1713, CLT 1738, Bayes’ thm 1763, scan statistics 1767, latin sq 1782, sampling/surveys (The Bible)/1786, least squares 1805, normal distn 1809, Poisson process 1837, outlier detection 1852, Chebyshev ineq 1853, optimal design 1876, regression 1877, correlation 1888, Edgeworth expansion 1889, histogram 1891, mixture models 1894, Pearson family 1895, periodogram 1898, chi-sq test 1900, Gauss–Markov thm 1900, P-values 1900, Wiener process 1900, PCA 1901, Factor analysis 1904, meta analysis 1904, Lorenz curve 1905, t test 1908, maximum likelihood, 1912, variance stabilization 1915, SEM 1921, ANOVA 1921, suﬃciency 1922, Fisher–Yates test 1922, Pólya urns 1923, exchangeability 1924, Slutsky 1925, stable laws 1925, Fisher inf 1925, factorial designs 1926, normal extremes 1927, Wishart distn 1928, Control charts 1931, Neyman–Pearson tests 1933, K–S test 1933, martingales 1935, Exp family 1936, Fisher’s LDF 1936, Mahalanobis distance 1936, canonical corr 1936, conf intervals 1937, permutation tests 1937, F test 1937, Wilks’ thm 1938, large dev. 1938, Cornish-Fisher expansions 1938, Kendall’s τ 1938, Pitman estimates 1939, admissibility/minimaxity 1939, errors in variables 1940, BIBD 1940, Berry Esseen thm 1941, Wald test 1943, Itô integral 1944, Wilcoxon’s test 1945, SPRT 1945, Cramér–Rao ineq 1945, two stage estimators 1945, asymp normality MLE 1946, Jeﬀreys prior 1946, Plackett–Burman designs 1946, delta method 1946, resampling 1946, Monte Carlo 1946, Kendall and Stuart 1st ed 1946, Hunt–Stein thm 1946, Rao–Blackwell 1947, Mann Whitney test 1947, contingency table testing 1947, orthogonal arrays 1947, score test 1948, U statistics 1948, Anscombe residuals 1948, Pitman eﬃciency 1948, Bernstein–von Mises 1949, jackknife 1949, test for additivity 1949, Feller Vol I, 1950, Lehmann–Scheﬀe thm 1950, Durbin–Watson test 1950, NN classiﬁcation 1951, long range dep. 1951, invariance principle 1951, ARMA models 1951, thresholding 1952, Horvitz–Thompson est 1952, Lehmann’s TSH 1953, semiparametric models 1953, Scheﬀe intervals 1953, Whittle estimator 1953, MCMC 1953, cusum charts 1954, ranking and selection 1954, saddlepoint approx 1954, test for change point 1955, Basu’s thm 1955, shrinkage 1956, kernel density est 1956, empirical Bayes 1956, monotone likelihood ratio 1956, DKW 1956, adaptive inference 1956, Grenander est 1956, k-means clustering 1957, Roy’s root test 1957, Kaplan–Meier 1958, FDA 1958, Copulas 1959, D-optimality 1959, LAN 1960, Kalman ﬁlter 1960, HMM 1960, conjugate priors 1961, Bayes factor 1961, James Stein est 1961, Hartley–Rao method 1962, kriging 1963, variogram 1963, ridge regr. 1963, Monte Carlo tests 1963, M est 1964, nonparametric regression 1964, Box–Cox transformations 1964, growth curve models 1964, Shapiro–Wilk test 1965, random coeﬃcient regression 1965, Jolly–Seber models 1965, Bahadur expansion 1966, Bahadur slope 1967, robust Bayes 1967, total positivity 1968, q-q plot 1968, longitudinal data 1968, fractional Brownian motion 1968, Grubbs’ tests 1969, AIC 1969, repeated sig tests 1969, Box Jenkins method 1970, empirical risk min 1971, VC classes 1971, penalized density est 1971, proportional hazards 1972, Stein’s method 1972, GLM 1972, isotonic regression 1972, Stein’s identity 1973, Cp 1973, robust regression 1973, Ferguson priors 1973, inﬂuence function 1974, proj pursuit 1974, opt est eqns 1974, covariance regularization 1975, partial likelihood 1975, KMT embedding 1975, imputation 1976, CV 1977, EDA 1977, EM 1977, consistent nonparametric regression 1977, BIC 1978, quantile regression 1978, Donsker classes 1978, bootstrap 1979, reference priors 1979, unit root test 1979, bootstrap consistency 1981, Pickands dependence function 1981, ARCH 1982, graphical models 1983, magic formula 1983, propensity scores 1983, CART 1984, block bootstrap 1985, Chinese restaurant process 1985, Bayesian networks 1985, generalized est eqns 1986, prepivoting 1987, Daubechies wavelets 1988, EL 1988, multiresolution analysis 1989, landmark Gaussian distn 1989, boosting 1990, smoothing splines 1990, deconvolution ests 1990, SIR 1991, automatic bandwidths 1991, functional regression 1991, supersaturated designs 1993, local linear smoothers 1993, oracles 1994, bagging 1994, stationary bootstrap 1994, SureShrink 1995, reversible jump MCMC 1995, FDR 1995, soft margin SVM 1995, Lasso 1996, block thresholding 1999, LAR 2004, group lasso 2006, sparse PCA 2006, covariance banding and tapering 2008.

Breaking down these items into categories: descriptive statistics 1, books 3, sampling and design 11, non and semiparametrics 18, probability 36, parametric inference 66, models and methodology 80.

Let me also report a time series plot of occurrences of these developments in five-year intervals [see below]. We cannot expect that innovations have checked in at a uniform rate over 350 years. There are some seven major peaks in the plot around special periods, corresponding, apparently, to the Pearson age, the Fisher age, the optimality/nonparametrics age, the methodology age, the robustness/heavy math age, the bootstrap/computer age, and the HD age. Someone else’s list may produce other peaks.

With this, I say goodbye to my colleagues around the world. It was a joy and a learning experience. Thank you.

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