Du tout à la partie. L'âge d'or du sondage en Russie (1885-1924)

Mespoulet, Martine

doi:10.3406/receo.2000.3025

Cited by 4 publications

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“…They were then tried out in the field before being assessed at the next congress. Thus, in Russia, the methodology of sampling surveys was developed from the practice of regional administrative statistical surveys and was fed by the theoretical principles worked out and discussed in Russian statistics societies and at congresses (Mespoulet 2000).…”

Section: Discussion Among Statisticians About Random Samplingmentioning

confidence: 99%

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From Typical Areas to Random Sampling: Sampling Methods in Russia from 1875 to 1930

Mespoulet

2002

Science in Context

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ArgumentWhile we know that Russian mathematicians contributed to the application of probability in the theory of statistics, Western literature on the history of statistics generally overlooks the role played by statisticians working in zemstva statistics departments. This paper argues that the quantity and the diversity of statistical data needed by zemstva administrators stimulated methodological innovations in the field and influenced the rise and development of sampling surveys in Russia between 1875 and 1930. The first surveys on parts of the whole were done by statisticians who were seeking solutions to practical administrative problems, and their sampling techniques evolved as Russian administrators put these statistical surveys to use. Finally, the paper argues that Kovalevskiy’s mathematical treatment of the theory of stratified sampling, published in 1924, ten years before Jerzy Neyman’s, is in fact a synthesis of the zemstva statisticians’ sampling practice and the Russian university statisticians’ theoretical works before 1917.

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Section: Discussion Among Statisticians About Random Samplingmentioning

confidence: 99%

“…They were created in 1864 and abolished at the end of 1917. Their statistics departments played a leading role in the practice and methodology of sampling surveys in Russia (Mespoulet 2000).…”

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confidence: 99%

From Typical Areas to Random Sampling: Sampling Methods in Russia from 1875 to 1930

Mespoulet

2002

Science in Context

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“…En Nor-uega (Lie, 2001), las encuestas agrarias realizadas a mitad de los años 1870 por Kiaer y Mohn en el marco del Central Bureau of Statistics, se realizan en 5 granjas representativas de su township y son complementadas por estudios en profundidad de los registros de la población de 56 townships, considerados cada uno de ellos como representativos de todo un distrito. En Rusia, como ha mostrado Martine Mespoulet (2000), Kaufman y Chuprov practican desde los años 1880 una forma de extracciones sistemáticas a veces combinadas con la selección de áreas-típicas, mientras que en 1900 Gurev pone en práctica el método de la selección razonada en la encuesta de Vjatka, con un éxito confirmado por la concordancia con el censo de 1880. En estos distintos ejemplos, los estadísticos, a la hora de construir su muestra, todavía todavía parecen dudar entre la representatividad del individuo medio típico, en el sentido de Quetelet y Le Play, y el de una muestra dotada de una variabilidad similar a la de la población, por el simple efecto de una extracción realizada al azar, o de foftna sistemática.…”

Section: Las Investigaciones Representativas Antes De 1936unclassified

“…El método de la selección razonada, puesto en práctica por Gini y Galvani -y presentada en el IIS (Gini, 1928)-para seleccionar 29 distritos entre 214 utilizando el censo itahano de 1921, es discutido paso a paso y descalificado por Neyman (1934) quien, en ese mismo artículo, introduce los intervalos de confianza y enuncia los principios de la estratificación óptima (Fienberg y Tanur, 1996). Sobre esta cuestión, Neyman reconocerá que sus resultados habían sido anticipados por la escuela rusa, y en particular por Chuprov y Kovalevskij, una docena de años antes (Mespoulet, 2000). Sobre la cuestión de los intervalos de confianza, la disputa con Fisher que defiende su método de los intervalos fiduciarios, será más viva en tanto entre en consonancia con otras controversias sobre los cuadrados latinos y sobre los test estadísticos, en un contexto sensibilizado por la crisis de sucesión de Kart Pearson en el University Colleage.…”

Section: Las Investigaciones Representativas Antes De 1936unclassified

La introducción en Francia de los Métodos de sondeo aleatorio

Armatte¹

2004

EMP

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El texto que sigue^ está elaborado a partir de diferentes fuentes de información sobre la las primeras investigaciones por sondeo realizadas en Francia por instituciones como el INSEE, el INED y el IFOP, así como algunas otras más efímeras aparecidas entre el año 1938, cuando Stoetzel crea el IFOP, y 1954, año en la que Fierre Thionet abandona el servicio de sondeos del INSEE. La reciente desaparición de Fierre Thionet en abril de 2002 nos ha incitado a escribir este texto y a rendir un homenaje muy particular a sus trabajos sobre los sondeos y a una obra muy mal conocida. Este texto se apoya en diversas publicaciones y documentos de archivos, pero también sobre entrevistas realizadas a los principales actores de este periodo'como Fierre Thionet (1996), su predecesor Henri Bunle, su colega del INSEE, Raymond Lévy-Bruhl, o su sucesor en el servicio de sondeos Jacques Desabie^

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“…Thus, scholars who have researched the statistical output of Russian workers in this field, before and shortly after the October Revolution, tell us that at least one other name should be added to that list. A consensus seems to have been reached regarding the individual statistician in question (Mespoulet, 2000, pp. 32, 35–37; Sheynin, 2011 [1996], p. 135; Seneta, 1985, pp.…”

Section: Introductionmentioning

confidence: 99%

Chuprov and Neyman: Priority in Science and the Uneven Diffusion of Scientific Results

Lusinchi¹

2020

J Historical Sociology

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Priority in "discovery," which sometimes leads to eponymy, is a highly prized form of reward in the scientific community. Recognition of priority is a norm whose violation will bring opprobrium (e.g. suspicion of plagiarism) upon the offender. But in order for an idea to receive an attribution of novelty, and its author to be acknowledged, it must first be noticed. This essay is a case study of an innovation (formulas related to stratified sampling) in the field of mathematical statistics that was "overlooked" for many years by many. Unknowingly, Jerzy Neyman (1894-1981) "refound" these formulas a decade later (1933). When a statistician in 1950 uncovered the original idea and its author (A.A. Chuprov, 1874-1926), he contacted Neyman who promptly published a "Recognition of priority" (1952). The study examines the perplexing situation in which some results become known to and recognized by the statistical community, while others, originating from the very same paper, were "overlooked" by sampling statisticians (among others) who, unlike Neyman, had access to the paper and thus had ample opportunity to identify Chuprov's formulas as relevant to their work. Chuprov was well-known in the statistics world, and the publication in which he published his ideas (1923) was a respected statistical journal (Metron). How is it that it took nearly 20 years for someone in the statistics community to notice that Chuprov had anticipated Neyman in deriving the formulas in question?

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Du tout à la partie. L'âge d'or du sondage en Russie (1885-1924)

Cited by 4 publications

References 0 publications

From Typical Areas to Random Sampling: Sampling Methods in Russia from 1875 to 1930

From Typical Areas to Random Sampling: Sampling Methods in Russia from 1875 to 1930

La introducción en Francia de los Métodos de sondeo aleatorio

Chuprov and Neyman: Priority in Science and the Uneven Diffusion of Scientific Results

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