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Fisher and regression

Aldrich, John (2005) Fisher and regression Statistical Science, 20, (4), pp. 401-417. (doi:10.1214/088342305000000331).

Record type: Article

Abstract

In 1922 R.A. Fisher introduced the modern regression model, synthesizing the regression theory of Pearson and Yule and the least squares theory of Gauss. The innovation was based on Fisher’s realization that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of the development of statistical theory in the early twentieth century.

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Published date: 2005
Additional Information: Full text available logged in to Webcat
Keywords: fisher, karl pearson, bartlett, regression, theory of errors, correlation, ancillary statistic, history of statistics

Identifiers

Local EPrints ID: 34871
URI: http://eprints.soton.ac.uk/id/eprint/34871
ISSN: 0883-4237
PURE UUID: 2a1d75e0-f455-418c-ae33-e98e87e0b457

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Date deposited: 15 May 2006
Last modified: 17 Jul 2017 15:49

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Contributors

Author: John Aldrich

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