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November 2005 Fisher and Regression
John Aldrich
Statist. Sci. 20(4): 401-417 (November 2005). DOI: 10.1214/088342305000000331


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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John Aldrich. "Fisher and Regression." Statist. Sci. 20 (4) 401 - 417, November 2005.


Published: November 2005
First available in Project Euclid: 12 January 2006

zbMATH: 1130.62300
MathSciNet: MR2210227
Digital Object Identifier: 10.1214/088342305000000331

Keywords: ancillary statistic , Correlation , History of statistics , karl Pearson , M. S. Bartlett , R. A. Fisher , regression , theory of errors

Rights: Copyright © 2005 Institute of Mathematical Statistics

Vol.20 • No. 4 • November 2005
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