Article ID: CBB456363893

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

unapi

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
Panza, Marco
Aubusson de Cavarlay, Bruno
Beaud, Jean-Pierre
Echelbarger, Charles
Ferraro, Giovanni
Goldstein, Catherine
Journals
Archive for History of Exact Sciences
British Society for the History of Mathematics Bulletin
European Legacy
Histoire & Mesure
História, Ciências, Saúde---Manguinhos
Intellectual History Review
Publishers
Mathematical Association of America
Duke University
Librairie Philosophique J. Vrin
Routledge
Springer Nature
Concepts
Mathematics
Philosophy of mathematics
Algebra
Statistics
Geometry
Mathematics and its relationship to science
People
Descartes, René
Lagrange, Joseph Louis
Gauss, Carl Friedrich
Beeckman, Isaac
Boole, George
Ellis, Robert Leslie
Time Periods
19th century
20th century
18th century
17th century
20th century, early
21st century
Places
Great Britain
Brazil
Bengal (India)
Canada
Denmark
France
Institutions
University of Calcutta
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