Fisher and regression

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


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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
Digital Object Identifier (DOI): doi:10.1214/088342305000000331
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
ePrint ID: 34871
Accepted Date and Publication Date:
Date Deposited: 15 May 2006
Last Modified: 31 Mar 2016 12:02

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