Fisher and regression
Fisher and regression
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.
fisher, karl pearson, bartlett, regression, theory of errors, correlation, ancillary statistic, history of statistics
401-417
Aldrich, John
a8ab8666-24a2-4d98-83bb-6053438c00ee
November 2005
Aldrich, John
a8ab8666-24a2-4d98-83bb-6053438c00ee
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: November 2005
Keywords:
fisher, karl pearson, bartlett, regression, theory of errors, correlation, ancillary statistic, history of statistics
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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: 15 Mar 2024 07:49
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