Article ID: CBB456363893

Linear algebra and multivariate analysis in statistics: development and interconnections in the twentieth century (2022)


The most obvious points of contact between linear and matrix algebra and statistics are in the area of multivariate analysis. We review the way that, as both developed during the last century, the two influenced each other by examining a number of key areas. We begin with matrix and linear algebra, its emergence in the nineteenth century, and its eventual penetration into the undergraduate curriculum in the twentieth century. We continue with a similar account for multivariate analysis in statistics. We pick out the year 1936 for three key developments, and the early post-war period for three more. We then turn to some special results in linear algebra that we need. We briefly discuss four of the main contributors, and close with thirteen ‘case studies’, showing in a range of specific cases how these general algebraic methods have been put to good use and changed the face of statistics.

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Authors & Contributors
Kieldsen, Tinne Hoff
Ferreirós Domínguez, José
Gray, Jeremy
Prévost, Jean-Guy
Beaud, Jean-Pierre
Aubusson de Cavarlay, Bruno
Archive for History of Exact Sciences
Scientia Canadensis: Journal of the History of Canadian Science, Technology, and Medicine
Histoire & Mesure
História, Ciências, Saúde---Manguinhos
Journal Electronique d'Histoire des Probabilités et de la Statistique
Physis: Rivista Internazionale di Storia della Scienza
Oxford University Press
Harvard University Press
University of Pittsburgh
University of British Columbia (Canada)
Gangemi Editore
Philosophy of mathematics
Philosophy of science
Hilbert, David
Enriques, Federigo
Galton, Francis
Frege, Gottlob
Lagrange, Joseph Louis
Kant, Immanuel
Time Periods
19th century
20th century
18th century
20th century, early
21st century
Great Britain

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