Statistical Science

Fisher and Regression

John Aldrich

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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.

Article information

Source
Statist. Sci. Volume 20, Number 4 (2005), 401-417.

Dates
First available in Project Euclid: 12 January 2006

Permanent link to this document
http://projecteuclid.org/euclid.ss/1137076660

Digital Object Identifier
doi:10.1214/088342305000000331

Mathematical Reviews number (MathSciNet)
MR2210227

Zentralblatt MATH identifier
1130.62300

Citation

Aldrich, John. Fisher and Regression. Statistical Science 20 (2005), no. 4, 401--417. doi:10.1214/088342305000000331. http://projecteuclid.org/euclid.ss/1137076660.


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References

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