Karl Pearson and the Scandinavian School of Statistics

Guttorp, Peter; Lindgren, Georg

doi:10.1111/j.1751-5823.2009.00069.x

Cited by 9 publications

(9 citation statements)

References 28 publications

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“…He and Pearson had a heated exchange of publications, criticising each other. Charlier's critique agrees with Kapteyn's, but his words are more diplomatic (Guttorp & Lindgren, , p. 67).…”

Section: Statistics And/or Mathematical Statisticsmentioning

confidence: 59%

“…In Copenhagen, the Danish biologist Wilhelm Johannsen coined the name gene and explained how one could combine Mendelian inheritance with variation within population. Johannsen and Karl Pearson disagreed on fundamental statistical issues (Guttorp & Lindgren, ), but the contacts between Charlier and Johannsen seem to have concerned only the organisation of statistical teaching and research (Johannsen, ).…”

Section: Fahlbeck and Charliermentioning

confidence: 99%

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Why Distinguish Between Statistics and Mathematical Statistics–The Case of Swedish Academia

Guttorp

Lindgren

2018

Int Statistical Rev

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Summary A separation between the academic subjects statistics and mathematical statistics has existed in Sweden almost as long as there have been statistics professors. The same distinction has not been maintained in other countries. Why has it been kept for so long in Sweden, and what consequences may it have had? In May 2015, it was 100 years since Mathematical Statistics was formally established as an academic discipline at a Swedish university where Statistics had existed since the turn of the century. We give an account of the debate in Lund and elsewhere about this division during the first decades after 1900 and present two of its leading personalities. The Lund University astronomer (and mathematical statistician) C. V. L. Charlier was a leading proponent for a position in mathematical statistics at the university. Charlier's adversary in the debate was Pontus Fahlbeck, professor in political science and statistics, who reserved the word statistics for ‘statistics as a social science’. Charlier not only secured the first academic position in Sweden in mathematical statistics for his former PhD student Sven Wicksell but also demonstrated that a mathematical statistician can be influential in matters of state, finance as well as in different natural sciences. Fahlbeck saw mathematical statistics as a set of tools that sometimes could be useful in his brand of statistics. After a summary of the organisational, educational and scientific growth of the statistical sciences in Sweden that has taken place during the last 50 years, we discuss what effects the Charlier–Fahlbeck divergence might have had on this development.

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“…He and Pearson had a heated exchange of publications, criticising each other. Charlier's critique agrees with Kapteyn's, but his words are more diplomatic (Guttorp & Lindgren, , p. 67).…”

Section: Statistics And/or Mathematical Statisticsmentioning

confidence: 59%

Section: Fahlbeck and Charliermentioning

confidence: 99%

Why Distinguish Between Statistics and Mathematical Statistics–The Case of Swedish Academia

Guttorp

Lindgren

2018

Int Statistical Rev

Self Cite

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“…In Johannsen (1913) there are many references to Galton, and Pearson, as well as to Darwin, but fewer to Morgan. Johannsen, although a great supporter of statistical method in biology, was one of the leaders of a group of biologists opposing the views of Galton, Karl Pearson and Weldon on inheritance ( Guttorp and Lindgren, 2009 ). The conflict with Pearson started with Johannsen’s (1903) paper (see Peters, 1959 for a version in English).…”

Section: Discussionmentioning

confidence: 99%

On S.N. Bernstein's derivation of Mendel's Law and 'rediscovery' of the Hardy-Weinberg distribution

Stark

Seneta

2012

Genet. Mol. Biol.

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Around 1923 the soon-to-be famous Soviet mathematician and probabilist Sergei N. Bernstein started to construct an axiomatic foundation of a theory of heredity. He began from the premise of stationarity (constancy of type proportions) from the first generation of offspring. This led him to derive the Mendelian coefficients of heredity. It appears that he had no direct influence on the subsequent development of population genetics. A basic assumption of Bernstein was that parents coupled randomly to produce offspring. This paper shows that a simple model of non-random mating, which nevertheless embodies a feature of the Hardy-Weinberg Law, can produce Mendelian coefficients of heredity while maintaining the population distribution. How W. Johannsen’s monograph influenced Bernstein is discussed.

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“…Ce domaine de la statistique a été créé par le statisticien danois Kirstine Smith [2] [3]. Parmi les critères statistiques envisagés [4], le plus employé est la D-optimalité qui consiste à maximiser le déterminant de la matrice de Fisher (inverse de la matrice de variance covariance) afin de minimiser la variance des estimateurs et d'augmenter ainsi la précision des résultats obtenus à l'issue des prochains essais. Ainsi, les futurs essais sont choisis de manière à conforter l'estimation courante établie à partir des essais déjà réalisés.…”

Section: Planification Optimale Des Essais Par La Méthode D-optimaleunclassified

Amélioration de la méthode Neyer d'estimation de fiabilité des systèmes mono-coup (one shot) utilisée en pyrotechnie

Etcheverry¹,

Cabarbaye²,

Bosse³

et al. 2016

Congrès Lambda Mu 20 De Maîtrise Des Risques Et De Sûreté De Fonctionnement

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Cette communication présente des améliorations apportées à la méthode Neyer d'estimation de fiabilité des systèmes monocoup (one shot) utilisée notamment en pyrotechnie. Elle préconise l'utilisation d'un outil d'optimisation globale pour s'affranchir des optima multiples du déterminant de la matrice de Fisher et l'absence de simplification dans les calculs. Elle propose également de remplacer sa phase d'initialisation par la mise en oeuvre d'une technique bayésienne consistant à transformer la connaissance a priori en essais fictifs au moyen de deux boucles d'optimisation imbriquées. Désignée sous le nom de méthode "Caboum" et supportée par un outil (Gencab), cette méthode originale de planification optimale et d'exploitation des essais peutêtre généralisée à la plupart des plans d'expériences, dont les essais accélérés de fiabilité ou de dégradation, pour caractériser les courbes de réponse. Son efficacité a été démontrée par simulation.

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Karl Pearson and the Scandinavian School of Statistics

Abstract: The relationship between Karl Pearson and the Scandinavian statisticians was more of a competitive than a collaborative nature. We describe the leading statisticians and stochasticists of the Scandinavian school, and relate some of their work to the work of Pearson.

Cited by 9 publications

References 28 publications

Why Distinguish Between Statistics and Mathematical Statistics–The Case of Swedish Academia

Why Distinguish Between Statistics and Mathematical Statistics–The Case of Swedish Academia

On S.N. Bernstein's derivation of Mendel's Law and 'rediscovery' of the Hardy-Weinberg distribution

Amélioration de la méthode Neyer d'estimation de fiabilité des systèmes mono-coup (one shot) utilisée en pyrotechnie

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