Fisher and regression
Aldrich, John (2005) Fisher and regression. Statistical Science, 20, (4), 401-417. (doi:10.1214/088342305000000331).
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Description/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.
| Item Type: | Article |
|---|---|
| Additional Information: | Full text available logged in to Webcat |
| ISSNs: | 0883-4237 (print) |
| Related URLs: | |
| Keywords: | fisher, karl pearson, bartlett, regression, theory of errors, correlation, ancillary statistic, history of statistics |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | University Structure - Pre August 2011 > School of Social Sciences > Economics |
| Item ID: | 34871 |
| Date Deposited: | 15 May 2006 |
| Last Modified: | 01 Jun 2011 11:37 |
| Contributors: | Aldrich, John (Author) |
| Date: | 2005 |
| Additional Information: | Full text available logged in to Webcat |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/34871 |
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